# rl-list.com, RL Environment Vendor Directory, full dataset
Generated 2026-06-07. 38 vendors. Source: rl-list.com

## What this is
A machine-readable export of an independently-compiled directory of vendors building reinforcement-learning environments, agent evals, and human training data for AI labs. Paste it into an LLM to build a shortlist, compare vendors, or pressure-test a procurement decision.

## Read this before analysing
- FIRST-PASS overview only. Good for a shortlist / market map, NOT a final decision.
- Every figure comes from PUBLIC sources or data shared by vendors directly, so coverage is limited and uneven.
- For a real selection, request WORK SAMPLES from vendors and let those be the deciding factor.
- "unknown" means we could not source it publicly. It is NOT zero and NOT negative, do not infer a value.
- Per-field confidence tags: confirmed (primary/official source) | reported (credible third party) | estimated (clearly-labelled inference) | unknown (not found).
- Customers tagged "self-claimed" come from the vendor's own site (a claim, not proof); "verified" = corroborated by a third party.
- RFI internals (task/sample counts, pass@1, complexity tiers, harness, data format, unit/total pricing) are DELIBERATELY EXCLUDED, they are not public and only come from direct vendor engagement. Do not estimate them.
- Ranking: only dedicated commercial vendors are ranked, by the "RL List score" (scale & traction + signals + verification), with a few editorial placements. Incumbents, infrastructure and open-source projects are listed but NOT ranked.

## Suggested prompt
> "Here is a sourced, confidence-tagged directory of RL-environment vendors. Shortlist the best 3–5 for <our use case, budget, security/compliance needs, deployment model>. Prefer higher data confidence, explicitly flag where key fields are 'unknown', and list what work samples I should request to decide."

---
## Mechanize, rank #1
- slug: mechanize
- segment: Commercial vendors
- website: https://www.mechanize.work/
- focus_areas: Coding, Computer Use, Private Codebases
- positioning: Mechanize is a small, elite San Francisco vendor (founded April 2025 by ex-Epoch AI researchers Matthew Barnett, Tamay Besiroglu, and Ege Erdil) that builds a small number of robust, high-fidelity RL environments and evals for frontier coding agents, selling to leading AI labs. Its stated long-term mission is the full automation of valuable economic work via simulated 'digital office' environments.
- best_fit: A frontier lab seeking a small set of deep, hard software-engineering RL environments and evals built by elite engineers rather than high-volume crowdsourced data.
- overall_confidence: medium
- founded_year: 2025 [confirmed], source: https://www.mechanize.work/announcing-mechanize-inc/ (founded April 17, 2025; accessed 2026-06-07)
- status: active [confirmed], source: https://www.mechanize.work/ (accessed 2026-06-07)
- hq_location: San Francisco, USA [confirmed], source: https://www.linkedin.com/company/mechanize-inc (SF HQ) and https://tracxn.com/d/companies/mechanize (San Francisco; accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: no [reported], source: https://www.mechanize.work/apply (roles listed in-person San Francisco; accessed 2026-06-07)
- current_headcount: 38 employees (as of 2026-05-31); size band 11-50 [reported], source: https://tracxn.com/d/companies/mechanize (38 employees, as of 2026-05-31); LinkedIn shows 11-50 band; PitchBook reports ~25 (conflicting) (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/mechanize-inc (11-50 band) and Tracxn 38 employees (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: ~10 open roles (e.g. Software Engineer, Research Engineer (Alignment), Operations Generalist, Recruiter, Counsel, Executive Assistant) [reported], source: https://www.mechanize.work/apply (accessed 2026-06-07)
- has_researchers: yes [confirmed], source: Founders are ex-Epoch AI researchers; hiring Research Engineer (Alignment) per https://www.mechanize.work/apply (accessed 2026-06-07)
- researcher_count: unknown [unknown]
- researcher_backgrounds: Founders Matthew Barnett, Tamay Besiroglu, and Ege Erdil are co-founders/alumni of Epoch AI (an AI research institute Besiroglu co-founded in 2022) [confirmed], source: https://www.mechanize.work/announcing-mechanize-inc/ and https://techcrunch.com/2025/04/19/famed-ai-researcher-launches-controversial-startup-to-replace-all-human-workers-everywhere/ (accessed 2026-06-07)
- published_papers_or_benchmarks: GBA Eval, benchmark measuring whether coding agents can write a Game Boy Advance emulator within 24 hours [reported], source: https://www.mechanize.work/ (accessed 2026-06-07)
- total_raised: $9.1M disclosed (April 24, 2026) plus an earlier undisclosed angel round (April 2025) [reported], source: https://www.mechanize.work/press-releases/ ($9.1M, April 24, 2026); https://tracxn.com/d/companies/mechanize (angel round April 28, 2025, amount undisclosed) (accessed 2026-06-07)
- last_round: $9.1M, April 24, 2026 (stage not disclosed) [reported], source: https://www.mechanize.work/press-releases/ ('Mechanize raises $9.1M', April 24, 2026; no stage or investors named on page) (accessed 2026-06-07)
- notable_investors: Nat Friedman; Daniel Gross; Patrick Collison; Dwarkesh Patel; Sholto Douglas; Marcus Abramovitch; Jeff Dean [reported], source: https://www.mechanize.work/announcing-mechanize-inc/ (Nat Friedman, Daniel Gross, Patrick Collison, Dwarkesh Patel, Sholto Douglas, Marcus Abramovitch) and TechCrunch / press (Jeff Dean) (accessed 2026-06-07). Note: round-level investor list ($9.1M) not disclosed; these are early backers.
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: environments [confirmed], source: https://www.mechanize.work/ ('Environments and evals for frontier coding agents'; accessed 2026-06-07)
- open_source: no [estimated], source: No public OSS repos found for their environments; GBA Eval referenced as a benchmark but no license/repo confirmed (accessed 2026-06-07)
- license: unknown [unknown]
- deployment_model: unknown [unknown]
- maturity: unknown [unknown]
- notable_customers: Anthropic (self-claimed, frontier-lab tie) [reported], source: https://techcrunch.com/2025/09/21/silicon-valley-bets-big-on-environments-to-train-ai-agents/ ('Mechanize has already been working with Anthropic on RL environments, two sources familiar with the matter told TechCrunch'; both companies declined to comment) (accessed 2026-06-07). Anonymous-sourced, unconfirmed by either party, not independently verified.
- sources:
  - https://www.mechanize.work/ (accessed 2026-06-07)
  - https://www.mechanize.work/announcing-mechanize-inc/ (accessed 2026-06-07)
  - https://www.mechanize.work/apply (accessed 2026-06-07)
  - https://www.mechanize.work/press-releases/ (accessed 2026-06-07)
  - https://www.linkedin.com/company/mechanize-inc (accessed 2026-06-07)
  - https://techcrunch.com/2025/09/21/silicon-valley-bets-big-on-environments-to-train-ai-agents/ (accessed 2026-06-07)
  - https://techcrunch.com/2025/04/19/famed-ai-researcher-launches-controversial-startup-to-replace-all-human-workers-everywhere/ (accessed 2026-06-07)
  - https://tracxn.com/d/companies/mechanize/__Zj76EY9-Iuwd7s9iR3MxAfLvnovzofl38AL66MgNwrQ (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/846556-03 (accessed 2026-06-07)
  - https://the-decoder.com/mechanize-is-building-digital-offices-to-train-ai-agents-to-fully-automate-computer-work/ (accessed 2026-06-07)

## AfterQuery, rank #2
- slug: afterquery
- segment: Commercial vendors
- website: https://www.afterquery.com
- focus_areas: Coding, Computer Use, Enterprise Workflows
- positioning: AfterQuery is a San Francisco applied-research lab and data platform (YC W25) that supplies frontier AI labs with expert-generated human data (SFT, RL rubrics), agent/RL environments, and computer-use trajectories, drawn from a large network of verified practitioners. It publishes real-task benchmarks such as Terminal-Bench, VADER, FinanceQA, and IDE-Bench, positioning around capturing how domain experts (engineers, financial analysts, lawyers) reason.
- best_fit: A frontier or enterprise AI team needing expert-authored RL environments, post-training data, and realistic real-task benchmarks across code, finance, and professional workflows.
- overall_confidence: medium
- founded_year: 2025 [confirmed], source: https://www.ycombinator.com/companies/afterquery (accessed 2026-06-07); https://siliconangle.com/2026/04/10/ai-training-data-startup-afterquery-nabs-30m-investment/ (accessed 2026-06-07), founded Jan/Feb 2025, YC W25
- status: active [confirmed], source: https://www.afterquery.com (accessed 2026-06-07); https://www.businesswire.com/news/home/20260409469482/en/AfterQuery-Raises-$30-Million-Series-A-Round-at-$300-Million-Valuation (accessed 2026-06-07)
- hq_location: San Francisco, USA [confirmed], source: https://www.ycombinator.com/companies/afterquery (accessed 2026-06-07); https://www.afterquery.com/careers (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: no [reported], source: https://www.afterquery.com/careers (accessed 2026-06-07), open roles listed as San Francisco; note core expert-data workforce (~100k practitioners) is distributed but corporate roles are SF-based
- current_headcount: ~126-140 employees (Tracxn 126 as of 2026-04-30; LinkedIn/aggregators ~136-140) [reported], source: https://tracxn.com/d/companies/afterquery (accessed 2026-06-07); https://www.linkedin.com/company/afterquery (public snippet, accessed 2026-06-07)
- headcount_band: 51-200 [reported], source: https://www.linkedin.com/company/afterquery (accessed 2026-06-07); https://tracxn.com/d/companies/afterquery (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: 24 [reported], source: https://www.afterquery.com/careers (accessed 2026-06-07), count taken from careers page snapshot; not independently verifiable post-access
- has_researchers: yes [confirmed], source: https://arxiv.org/abs/2505.19395 (accessed 2026-06-07); https://arxiv.org/abs/2601.11868 (accessed 2026-06-07), published arXiv benchmarks (VADER, Terminal-Bench) and Research roles on careers page
- researcher_count: unknown (2 open Research roles; benchmark-paper authors exist but team count not enumerated) [unknown], source: https://www.afterquery.com/careers (accessed 2026-06-07)
- researcher_backgrounds: Founders: Spencer Mateega (ex-Meta, ex-Google, Morgan Stanley/Silver Lake; Wharton/Penn), Carlos Georgescu (ex-Citadel Securities, ex-Meta, ex-Google), Danny Tang; Founding team / network cites prior roles at Goldman Sachs, McKinsey, Jane Street, Palantir, NVIDIA, Google [reported], source: https://www.ycombinator.com/launches/Mm5-afterquery-high-quality-ai-starts-with-high-quality-human-data (accessed 2026-06-07); https://www.afterquery.com/careers (accessed 2026-06-07)
- published_papers_or_benchmarks: VADER: A Human-Evaluated Benchmark for Vulnerability Assessment, Detection, Explanation, and Remediation (arXiv:2505.19395); Terminal-Bench / Terminal-Bench 2.0 (arXiv:2601.11868); FinanceQA: A Benchmark for Evaluating Financial Analysis Capabilities in LLMs (arXiv:2501.18062; github.com/AfterQuery/FinanceQA); IDE-Bench (github.com/AfterQuery/ide-bench) [confirmed], source: https://arxiv.org/abs/2505.19395 (accessed 2026-06-07); https://arxiv.org/abs/2601.11868 (accessed 2026-06-07); https://github.com/AfterQuery (accessed 2026-06-07)
- total_raised: $30.5M ($0.5M pre-seed 2025 + $30M Series A 2026) [confirmed], source: https://www.crunchbase.com/funding_round/afterquery-pre-seed--696021d4 (accessed 2026-06-07); https://www.businesswire.com/news/home/20260409469482/en/AfterQuery-Raises-$30-Million-Series-A-Round-at-$300-Million-Valuation (accessed 2026-06-07)
- last_round: Series A, $30M, announced 2026-04-09 [confirmed], source: https://www.businesswire.com/news/home/20260409469482/en/AfterQuery-Raises-$30-Million-Series-A-Round-at-$300-Million-Valuation (accessed 2026-06-07); https://siliconangle.com/2026/04/10/ai-training-data-startup-afterquery-nabs-30m-investment/ (accessed 2026-06-07)
- notable_investors: Altos Ventures (lead, Series A); The Raine Group; Y Combinator; BoxGroup; Latitude Capital; Angel investors from Google DeepMind, OpenAI, Anthropic, Meta Superintelligence Labs, Microsoft AI [confirmed], source: https://www.businesswire.com/news/home/20260409469482/en/AfterQuery-Raises-$30-Million-Series-A-Round-at-$300-Million-Valuation (accessed 2026-06-07); https://www.ycombinator.com/launches/Mm5-afterquery-high-quality-ai-starts-with-high-quality-human-data (accessed 2026-06-07)
- valuation: $300M post-money (Series A) [confirmed], source: https://www.businesswire.com/news/home/20260409469482/en/AfterQuery-Raises-$30-Million-Series-A-Round-at-$300-Million-Valuation (accessed 2026-06-07)
- revenue_signals: $100M+ annual revenue run rate (company-stated, ~14 months from founding) [reported], source: https://www.businesswire.com/news/home/20260409469482/en/AfterQuery-Raises-$30-Million-Series-A-Round-at-$300-Million-Valuation (accessed 2026-06-07), figure originates from the company, repeated in press, not independently audited
- soc2: unknown [unknown], source: https://www.afterquery.com (accessed 2026-06-07), no trust/security page or SOC2 claim found
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: https://www.afterquery.com (accessed 2026-06-07), no dedicated security/trust page found
- what_they_sell: mixed [confirmed], source: https://www.afterquery.com (accessed 2026-06-07), expert human data (SFT, RL rubrics), agent/RL environments, computer-use trajectories, and benchmarks
- open_source: yes [confirmed], source: https://github.com/AfterQuery (accessed 2026-06-07), public benchmarks (VADER, FinanceQA, IDE-Bench) and Harbor RL-environment framework
- license: Apache-2.0 (Harbor RL-environment framework); other repos vary/unspecified [reported], source: https://github.com/AfterQuery/harbor (accessed 2026-06-07), license per Harbor repo; not independently re-confirmed across all repos
- deployment_model: managed-hosted (data + RL environments delivered as a service to AI labs); open-source frameworks available (Harbor) [estimated], source: https://www.afterquery.com (accessed 2026-06-07); https://github.com/AfterQuery/harbor (accessed 2026-06-07)
- maturity: GA [estimated], source: https://www.afterquery.com (accessed 2026-06-07); https://www.businesswire.com/news/home/20260409469482/en/AfterQuery-Raises-$30-Million-Series-A-Round-at-$300-Million-Valuation (accessed 2026-06-07), commercially selling to AI labs with stated $100M+ run rate; product maturity not formally labeled by vendor
- notable_customers: Frontier AI labs (unnamed; company claims 'every leading AI lab' is a customer; press separately names OpenAI, Anthropic, Google as labs it serves, but without third-party confirmation) (self-claimed, frontier-lab tie) [reported], source: https://www.businesswire.com/news/home/20260409469482/en/AfterQuery-Raises-$30-Million-Series-A-Round-at-$300-Million-Valuation (accessed 2026-06-07); https://www.afterquery.com (accessed 2026-06-07), no individually verified named customer; claims trace to vendor
- sources:
  - https://www.afterquery.com (accessed 2026-06-07)
  - https://www.afterquery.com/careers (accessed 2026-06-07)
  - https://www.afterquery.com/blog/terminal-bench-improvement (accessed 2026-06-07)
  - https://www.ycombinator.com/companies/afterquery (accessed 2026-06-07)
  - https://techfundingnews.com/afterquery-gets-30m-from-altos-ventures-to-help-ai-understand-real-world-problems-better/ (accessed 2026-06-07)
  - https://startupintros.com/orgs/afterquery (accessed 2026-06-07)
  - https://www.linkedin.com/company/afterquery (accessed 2026-06-07)
  - https://tracxn.com/d/companies/afterquery (accessed 2026-06-07)
  - https://github.com/AfterQuery (accessed 2026-06-07)
  - https://github.com/AfterQuery/harbor (accessed 2026-06-07)
  - https://arxiv.org/abs/2505.19395 (accessed 2026-06-07)
  - https://arxiv.org/abs/2601.11868 (accessed 2026-06-07)
  - https://sacra.com/c/afterquery/ (accessed 2026-06-07)

## Deeptune, rank #3
- slug: deeptune
- segment: Commercial vendors
- website: https://deeptune.com
- focus_areas: Coding, Computer Use, Enterprise Workflows, Private Codebases
- positioning: Deeptune is a New York-based startup building managed reinforcement-learning environments ('training gyms') for computer-use and code, where AI agents practice and are evaluated on realistic digital knowledge-work tasks (simulating tools like Slack and Salesforce). It sells these pre-built environments primarily to frontier AI labs and raised a $43M Series A led by a16z, announced March 2026.
- best_fit: Frontier labs and model teams needing ready-made, managed RL environments for training/evaluating computer-use and coding agents.
- overall_confidence: medium
- founded_year: ~2025 per official Series A blog ('since we started one year ago', Mar 2026); aggregators (Tracxn, CB Insights) and LinkedIn list 2022, conflict, leaning 2025 per primary source [reported], source: https://deeptune.com/blog/series-a/ ; https://www.linkedin.com/company/trydeeptune accessed 2026-06-07
- status: active [confirmed], source: https://deeptune.com/blog/series-a/ accessed 2026-06-07
- hq_location: New York, NY, USA [confirmed], source: https://fortune.com/2026/03/19/andreessen-horowitz-ai-startups-deeptune-series-a/ accessed 2026-06-07
- other_locations: India (remote Member of Technical Staff role posted; a job posting, not a confirmed office) [reported], source: https://jobs.ashbyhq.com/deeptune accessed 2026-06-07
- distributed_remote: partial, NYC team described as in-person; some remote roles posted (e.g. India) [reported], source: https://jobs.ashbyhq.com/deeptune ; https://fortune.com/2026/03/19/andreessen-horowitz-ai-startups-deeptune-series-a/ accessed 2026-06-07
- current_headcount: ~20-25 (Fortune: 'roughly 20-person'; LinkedIn snippet: 25) [reported], source: https://fortune.com/2026/03/19/andreessen-horowitz-ai-startups-deeptune-series-a/ ; https://www.linkedin.com/company/trydeeptune accessed 2026-06-07
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/trydeeptune accessed 2026-06-07
- headcount_growth: unknown [unknown]
- open_roles_count: ~6 roles posted (e.g. Founding Recruiter, 2x Member of Technical Staff incl. India, Strategic Projects Lead, Founding Operations, open 'Build Your Role') [reported], source: https://jobs.ashbyhq.com/deeptune accessed 2026-06-07
- has_researchers: yes [reported], source: https://a16z.com/announcement/investing-in-deeptune/ accessed 2026-06-07
- researcher_count: unknown [unknown]
- researcher_backgrounds: Team includes engineers/operators from Anthropic, Scale AI, Palantir, Hebbia, Glean, Retool, Modal (per company/press); CEO/co-founder Tim Lupo: ex-Hebbia founding engineer, USC CS & Business; Co-founder/CTO Lukas Schmit (per Crunchbase and press) [reported], source: https://fortune.com/2026/03/19/andreessen-horowitz-ai-startups-deeptune-series-a/ ; https://www.crunchbase.com/person/lukas-schmit ; https://www.linkedin.com/in/timlup/ accessed 2026-06-07
- published_papers_or_benchmarks: No own papers/benchmarks published; a16z post references third-party benchmarks OSWorld and Terminal-Bench as targets Deeptune environments help improve (cites Opus 4.6 ~72.7% and GPT-5.4 ~75% on OSWorld) [reported], source: https://a16z.com/announcement/investing-in-deeptune/ accessed 2026-06-07
- total_raised: ~$43M (latest/likely only round). NOTE: value reflects the Series A round; lifetime total is uncertain, aggregators conflict (Tracxn/CB Insights $46.1M, PitchBook $42.2M) [reported], source: https://deeptune.com/blog/series-a/ ; https://tracxn.com/d/companies/deeptune/__oi3tMd7lIKO3Yo_B0aq6tBQHcjZSfLMnyHdwbaOa0SE accessed 2026-06-07
- last_round: Series A, $43M, announced March 19, 2026 (Crunchbase lists round date Feb 23, 2026) [confirmed], source: https://deeptune.com/blog/series-a/ ; https://a16z.com/announcement/investing-in-deeptune/ ; https://fortune.com/2026/03/19/andreessen-horowitz-ai-startups-deeptune-series-a/ accessed 2026-06-07
- notable_investors: Andreessen Horowitz (a16z, lead); 776; Abstract Ventures; Inspired Capital; Noam Brown (angel, OpenAI); Brendan Foody (angel, Mercor CEO); Yash Patil (angel, Applied Compute CEO) [confirmed], source: https://deeptune.com/blog/series-a/ ; https://fortune.com/2026/03/19/andreessen-horowitz-ai-startups-deeptune-series-a/ accessed 2026-06-07
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: environments [confirmed], source: https://a16z.com/announcement/investing-in-deeptune/ accessed 2026-06-07
- open_source: no [estimated]
- license: unknown [unknown]
- deployment_model: managed-hosted / API (pre-built 'training gyms' integrate in 'a few lines of code'; gyms come with problems, datasets, and infrastructure); customers are frontier labs [reported], source: https://deeptune.com/ accessed 2026-06-07
- maturity: GA [estimated], source: https://deeptune.com/blog/series-a/ accessed 2026-06-07
- notable_customers: Leading/frontier AI labs (unnamed; company claims '100s of gyms' built for them and contributions to recent computer-use advances) (self-claimed, frontier-lab tie) [reported], source: https://deeptune.com/ ; https://a16z.com/announcement/investing-in-deeptune/ accessed 2026-06-07
- sources:
  - https://deeptune.com/ (accessed 2026-06-07)
  - https://deeptune.com/blog/series-a/ (accessed 2026-06-07)
  - https://a16z.com/announcement/investing-in-deeptune/ (accessed 2026-06-07)
  - https://fortune.com/2026/03/19/andreessen-horowitz-ai-startups-deeptune-series-a/ (accessed 2026-06-07)
  - https://siliconangle.com/2026/03/19/deeptune-raises-43m-accelerate-ai-learning-virtual-training-gyms/ (accessed 2026-06-07)
  - https://www.linkedin.com/company/trydeeptune (accessed 2026-06-07)
  - https://jobs.ashbyhq.com/deeptune (accessed 2026-06-07)
  - https://www.linkedin.com/in/timlup/ (accessed 2026-06-07)
  - https://x.com/a16z/status/2034694854123692462 (accessed 2026-06-07)
  - https://tracxn.com/d/companies/deeptune/__oi3tMd7lIKO3Yo_B0aq6tBQHcjZSfLMnyHdwbaOa0SE (accessed 2026-06-07)

## Bespoke Labs, rank #4
- slug: bespoke-labs
- segment: Commercial vendors
- website: https://www.bespokelabs.ai/
- focus_areas: Long-Horizon
- positioning: Bespoke Labs is an applied AI research lab (Mountain View, CA, founded 2024) focused on data curation and RL-environment curation for training and evaluating agents, known for open datasets and reproducible recipes (OpenThoughts) and open-source tools (Curator, Evalchemy). It pairs a public open-source/open-data presence with commercial custom data and RL-environment delivery.
- best_fit: Buyers needing reasoning-focused data curation, open reproducible datasets/recipes, and custom RL-environment/eval data delivery from a research-led team.
- overall_confidence: medium
- founded_year: 2024 [reported], source: https://tracxn.com/d/companies/bespokelabs (accessed 2026-06-07); SEC Form D filed 2024-06-04 https://www.formds.com/issuers/bespokelabs-ai-inc (accessed 2026-06-07)
- status: active [confirmed], source: https://www.bespokelabs.ai/about-us (accessed 2026-06-07); active OSS releases and hiring on https://jobs.ashbyhq.com/bespokelabs (accessed 2026-06-07)
- hq_location: Mountain View, California, USA [confirmed], source: https://www.linkedin.com/company/bespokelabsai (public snippet: 800 W El Camino Real, Mountain View, CA 94040, accessed 2026-06-07); SEC Form D lists Santa Clara, CA
- other_locations: unknown [unknown]
- distributed_remote: yes [reported], source: https://jobs.ashbyhq.com/bespokelabs (some roles open to remote in the US, accessed 2026-06-07)
- current_headcount: ~40-48 employees (40 as of 2026-04-30 per Tracxn; ~48 profiles listed on LinkedIn page) [reported], source: https://www.linkedin.com/company/bespokelabsai (48 employees listed, accessed 2026-06-07); https://tracxn.com/d/companies/bespokelabs (40 as of 2026-04-30, accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/bespokelabsai (accessed 2026-06-07); Tracxn 40 employees as of 2026-04-30
- headcount_growth: unknown (LinkedIn growth posts reference recent hiring but no formal % disclosed) [unknown], source: https://www.linkedin.com/company/bespokelabsai (accessed 2026-06-07)
- open_roles_count: several open roles (e.g. RL Environments, Research Engineer, Data Operations Manager, DevOps Engineer, Technical Recruiter) on Ashby; exact count not reliably extractable from public page [reported], source: https://jobs.ashbyhq.com/bespokelabs (accessed 2026-06-07)
- has_researchers: yes [confirmed], source: https://www.bespokelabs.ai/about-us (self-described 'applied AI research lab'; team from Google/DeepMind, UC Berkeley, Stanford, NYU; multiple published works, accessed 2026-06-07)
- researcher_count: unknown (research-led team; exact count not extractable from public team page) [unknown], source: https://www.bespokelabs.ai/about-us (accessed 2026-06-07)
- researcher_backgrounds: Co-founder/CEO Maheswaran (Mahesh) Sathiamoorthy, ex-Google DeepMind; Co-founder/Chief Scientist Georgios (Alex) Dimakis, Professor, UC Berkeley (formerly UT Austin); Team members with backgrounds from Google, UC Berkeley, Stanford, NYU, Microsoft, Scale AI, AI2 (per vendor about-us page) [reported], source: https://www.bespokelabs.ai/about-us (vendor-stated; founder roles corroborated by https://www.linkedin.com/in/alex-dimakis-b1b20320/ and Tracxn founders page, accessed 2026-06-07)
- published_papers_or_benchmarks: OpenThoughts / OpenThoughts-114k, open reasoning dataset (collaboration with DataComp community; 190+ public models trained on it per GitHub); Bespoke Curator, synthetic data curation library; Evalchemy, evaluation/benchmark tooling; Bespoke-Stratos / OpenThinker reasoning models; Bespoke-MiniCheck, factuality model [reported], source: https://github.com/open-thoughts/open-thoughts; https://github.com/bespokelabsai/curator; https://www.bespokelabs.ai/ (accessed 2026-06-07)
- total_raised: $7.25M (SEC Form D: $7,249,998 sold) [confirmed], source: https://www.formds.com/issuers/bespokelabs-ai-inc (Form D filed 2024-06-04, accessed 2026-06-07)
- last_round: ~$7.25M raised ~May/June 2024; round stage ambiguous across sources (Luma/Form D context suggest Seed; Tracxn/Crunchbase label Series A 2024-05-22) [reported], source: https://www.formds.com/issuers/bespokelabs-ai-inc (Form D filed 2024-06-04); https://tracxn.com/d/companies/bespokelabs (Series A label); https://luma.com/36sbgxgo ('$7.25M Seed') (all accessed 2026-06-07)
- notable_investors: unknown [unknown], source: No investor names disclosed in public sources reviewed (Crunchbase profile inaccessible; Tracxn/PitchBook do not surface named lead investors). SEC Form D lists directors Georgios Alex Dimakis, Maheswaran Sathiamoorthy, Bhaskar Ghosh, and Priyank Patel but does not name investors. https://www.formds.com/issuers/bespokelabs-ai-inc (accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: mixed (data/RL-environment curation, open datasets and evals, and custom data delivery to enterprises and labs) [reported], source: https://www.bespokelabs.ai/ (vendor self-description, accessed 2026-06-07); https://github.com/bespokelabsai (OSS tooling, accessed 2026-06-07)
- open_source: yes [confirmed], source: https://github.com/bespokelabsai (accessed 2026-06-07)
- license: Apache-2.0 (Curator, SkyRL); MIT (Verifiers fork); OpenThinker/OpenThoughts artifacts Apache-2.0 [confirmed], source: https://github.com/bespokelabsai (accessed 2026-06-07)
- deployment_model: mixed, open-source libraries/datasets (self-hosted) plus custom data/RL-environment delivery via direct engagement; Curator integrates with provider APIs (OpenAI/Anthropic, etc.) [reported], source: https://www.bespokelabs.ai/; https://github.com/bespokelabsai/curator (accessed 2026-06-07)
- maturity: GA (open-source tools publicly available; commercial data delivery via direct contracts) [estimated], source: https://github.com/bespokelabsai/curator (Apache-2.0, 1.6k+ stars; PyPI package published, accessed 2026-06-07)
- notable_customers: Fortune 500 enterprises (unnamed) (self-claimed); Frontier labs / top labs (unnamed) (self-claimed, frontier-lab tie); Model builders using OpenThoughts datasets (190+ public HF models; unnamed) (self-claimed) [reported], source: https://www.bespokelabs.ai/ ('Fortune 500 enterprises and frontier labs trust us'); https://github.com/open-thoughts/open-thoughts (190+ public models). No specific named customers disclosed or third-party verified. (accessed 2026-06-07)
- sources:
  - https://www.bespokelabs.ai/ (accessed 2026-06-07)
  - https://www.bespokelabs.ai/about-us (accessed 2026-06-07)
  - https://www.linkedin.com/company/bespokelabsai (accessed 2026-06-07)
  - https://tracxn.com/d/companies/bespokelabs/__TgeW4_XxZv-sKUrOh6M6QeTLr6e9xHzW26BbTJzHYbQ (accessed 2026-06-07)
  - https://www.formds.com/issuers/bespokelabs-ai-inc (accessed 2026-06-07)
  - https://luma.com/36sbgxgo (accessed 2026-06-07)
  - https://github.com/bespokelabsai (accessed 2026-06-07)
  - https://jobs.ashbyhq.com/bespokelabs (accessed 2026-06-07)
  - https://newsletter.semianalysis.com/p/rl-environments-and-rl-for-science (accessed 2026-06-07)

## Huzzle Labs, rank #5
- slug: huzzle-labs
- segment: Commercial vendors
- website: https://labs.huzzle.com/
- focus_areas: Coding, Computer Use, Enterprise Workflows, Long-Horizon, Private Codebases
- positioning: Huzzle Labs is the AI division of London-based talent platform Huzzle (founded ~2020 by Ingmar Klein, Parham Rakhshanfar, and Amit Choudhary). It positions itself as a human-intelligence data foundry that builds RL environments (code, tool-use, computer-use, long-horizon enterprise workflows), expert trajectory data, and contextual evaluations for frontier AI labs and regulated European enterprises, leveraging Huzzle's vetted PhD/expert network. It bundles environments, human data, and evals in one stack.
- best_fit: Frontier labs and regulated enterprises needing custom RL environments plus expert human trajectory data and evals for code, computer-use, and long-horizon professional workflows.
- overall_confidence: medium
- founded_year: 2020 [reported], source: Search consensus (theorg.com, Tracxn, press) gives founding year 2020 by Ingmar Klein, Parham Rakhshanfar, and Amit Choudhary; refers to parent Huzzle. Conflicting aggregator dates (2021) exist. Labs is a later AI pivot (~2025). (accessed 2026-06-07)
- status: active [confirmed], source: https://labs.huzzle.com/ (accessed 2026-06-07); https://webflow.huzzle.com/aix (accessed 2026-06-07)
- hq_location: London, United Kingdom [reported], source: https://github.com/huzzle-app (accessed 2026-06-07); Tracxn registered address 85 Great Portland Street, London (accessed 2026-06-07)
- other_locations: Berlin, Germany; United States (operations) [reported], source: https://webflow.huzzle.com/aix (accessed 2026-06-07), US and European (Berlin) operations; bebee.com job posting also lists San Francisco (accessed 2026-06-07)
- distributed_remote: yes [reported], source: https://webflow.huzzle.com/aix (accessed 2026-06-07), operations across US and Europe running 'around the clock'; bebee.com role open to remote (accessed 2026-06-07)
- current_headcount: ~30 (15 engineers + 15 operators) for the Labs/AI division per vendor; parent Huzzle.com aggregators report ~81-93 [reported], source: https://webflow.huzzle.com/aix (accessed 2026-06-07), vendor self-description of Labs team size; parent figures from Tracxn/CBInsights aggregators
- headcount_band: 11-50 [reported], source: https://webflow.huzzle.com/aix (accessed 2026-06-07), vendor states 15 engineers + 15 operators for Labs. Parent-company aggregator figure of ~81-93 reflects the larger talent-platform entity, not the Labs division.
- headcount_growth: Parent Huzzle reportedly ranked among Sifted 100 UK & Ireland 2026 fastest-growing startups; Labs-specific growth not separately disclosed [reported], source: https://sifted.eu/leaderboards/sifted-100-uk-ireland-2026 (accessed 2026-06-07), applies to parent Huzzle, ranking via secondary sources; downgraded as the #7 figure is from a job-posting claim, not primary confirmation
- open_roles_count: ~44 open positions (parent Huzzle, 2026) [reported], source: https://apply.workable.com/huzzle/ (accessed 2026-06-07); Sifted/Glassdoor snippets, parent company, not Labs-specific
- has_researchers: yes [confirmed], source: Confirmed by Huzzle Labs (company-provided), accessed 2026-06-07
- researcher_count: ~15 engineers plus a vetted external PhD/expert network (size of dedicated research staff not separately disclosed) [reported], source: https://webflow.huzzle.com/aix (accessed 2026-06-07)
- researcher_backgrounds: RL engineer, ex-Turing; Researchers from IIT Kharagpur and IIT Bombay (incl. PhD); Ex post-training lead on BharatGen’s 2.9B-parameter PARAM-1 LLM [confirmed], source: Confirmed by Huzzle Labs (company-provided), accessed 2026-06-07
- published_papers_or_benchmarks: OpenEnv, visual-memory spreadsheet environment, published with Meta [confirmed], source: https://labs.huzzle.com/blog/openenv-visual-memory-spreadsheet (accessed 2026-06-07)
- total_raised: $6M [confirmed], source: Confirmed by Huzzle Labs (company-provided), accessed 2026-06-07
- last_round: $6M [confirmed], source: Confirmed by Huzzle Labs (company-provided), accessed 2026-06-07
- notable_investors: 10x Founders; Angel Invest; Emerge; Former CTO of Hugging Face (angel); Researchers at Meta (angels); Researchers at Applied Intuition (angels) [confirmed], source: Confirmed by Huzzle Labs (company-provided), accessed 2026-06-07
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: Type II [confirmed], source: https://huzzle.secureframetrustuk.com/#compliance-d852f4b3-d3ac-4c7e-9e48-bb30d52d89c9, Huzzle Labs trust center (Secureframe), accessed 2026-06-07
- other_certifications: unknown [unknown]
- security_page: https://huzzle.secureframetrustuk.com/#compliance-d852f4b3-d3ac-4c7e-9e48-bb30d52d89c9 [confirmed], source: https://huzzle.secureframetrustuk.com/#compliance-d852f4b3-d3ac-4c7e-9e48-bb30d52d89c9, Huzzle Labs trust center (Secureframe), accessed 2026-06-07
- what_they_sell: mixed [confirmed], source: https://labs.huzzle.com/ (accessed 2026-06-07); https://webflow.huzzle.com/aix (accessed 2026-06-07), RL environments, expert human trajectory data, and contextual evals in one stack
- open_source: partial [reported], source: https://labs.huzzle.com/blog/openenv-visual-memory-spreadsheet (accessed 2026-06-07), OpenEnv environment published openly with Meta; core products otherwise proprietary
- license: unknown [unknown]
- deployment_model: unknown [unknown]
- maturity: unknown [unknown]
- notable_customers: Apple (self-claimed); Lazard (self-claimed); Financial Times (self-claimed) [reported], source: https://webflow.huzzle.com/aix (accessed 2026-06-07), listed on vendor's own site; no third-party confirmation found. Vendor also references unnamed 'frontier AI labs' as partners.
- sources:
  - https://labs.huzzle.com/blog/openenv-visual-memory-spreadsheet (accessed 2026-06-07)
  - https://huzzle.secureframetrustuk.com/#compliance-d852f4b3-d3ac-4c7e-9e48-bb30d52d89c9 (accessed 2026-06-07)
  - https://labs.huzzle.com/ (accessed 2026-06-07)
  - https://x.com/himanshustwts/status/2041877003251695733 (accessed 2026-06-07)
  - https://bebee.com/us/jobs/founding-engagement-manager-frontier-labs-huzzlecom--theirstack-649700226 (accessed 2026-06-07)
  - https://github.com/huzzle-app (accessed 2026-06-07)
  - https://www.eu-startups.com/2024/04/london-based-huzzle-secures-e1-67-million-pre-seed-to-help-students-land-their-dream-graduate-job/ (accessed 2026-06-07)
  - https://tech.eu/2024/04/18/meet-the-gen-z-founders-rewiring-the-graduate-job-market/ (accessed 2026-06-07)
  - https://tracxn.com/d/companies/huzzle/__gSmaXUdJfRlNTOIE3SEajswKR4IZuSyaJRpXk91s88g (accessed 2026-06-07)
  - https://sifted.eu/leaderboards/sifted-100-uk-ireland-2026 (accessed 2026-06-07)
  - https://www.linkedin.com/company/huzzle-com (accessed 2026-06-07)
  - https://www.hud.ai/resources/platforms-agent-evals-rl-training-data (accessed 2026-06-07)
  - https://alignlist.com/guides/top-40-rl-environments-startups-and-companies (accessed 2026-06-07)

## Fleet AI, rank #6
- slug: fleet-ai
- segment: Commercial vendors
- website: https://www.fleetai.com/
- focus_areas: Computer Use, Enterprise Workflows
- positioning: Fleet AI builds high-fidelity reinforcement-learning training environments ('gyms') that replicate enterprise software such as Salesforce and Excel, plus browser/desktop workflows, so frontier AI labs and large enterprises can train and evaluate computer-use agents. It ships a Python SDK, a platform API, and the open-source 'Harbor' agent-evaluation/RL-environment tooling, pairing simulated environments with human supervision.
- best_fit: A frontier lab or large enterprise that needs bespoke, high-fidelity RL environments simulating real enterprise software (CRM, spreadsheets, browser/desktop) to train and evaluate computer-use agents.
- overall_confidence: medium
- founded_year: 2024 [reported], source: https://www.kucoin.com/news/flash/ai-training-firm-fleet-eyes-750m-valuation-amid-60x-revenue-surge (accessed 2026-06-07); https://www.theinformation.com/newsletters/ai-agenda/reinforcement-learning-gym-startup-buoyed-labs-appetite-training-data-reaches-750-million-valuation (accessed 2026-06-07)
- status: active [confirmed], source: https://www.fleetai.com/ (accessed 2026-06-07); https://github.com/fleet-ai (accessed 2026-06-07), active site and recent OSS activity
- hq_location: New York, NY, USA [reported], source: https://www.linkedin.com/company/fleet-so (accessed 2026-06-07); https://sacra.com/c/fleet/ (accessed 2026-06-07), both list New York, NY; careers page conflictingly lists a San Francisco (SOMA) HQ
- other_locations: San Francisco, CA (careers page lists SOMA office, in conflict with NY HQ); Delray Beach / Chelsea-area secondary office (signals conflict: LinkedIn lists Delray Beach, FL; careers page lists New York/Chelsea) [reported], source: https://www.fleetai.com/careers (accessed 2026-06-07); https://www.linkedin.com/company/fleet-so (accessed 2026-06-07), location signals are inconsistent across sources
- distributed_remote: unknown [unknown], source: https://www.fleetai.com/careers (accessed 2026-06-07), multiple office locations are listed but no explicit remote/distributed policy is stated; prior 'yes' was an inference, not stated
- current_headcount: 11-50 per LinkedIn public company-size band as of 2026-06-07 (RocketReach ~41 is consistent); an earlier draft figure of ~133 could not be reproduced and appears erroneous [reported], source: https://www.linkedin.com/company/fleet-so (accessed 2026-06-07); https://rocketreach.co/fleet-ai-management_b6f95050c628d05e (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/fleet-so (accessed 2026-06-07), LinkedIn shows the '11-50 employees' size band
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: https://www.fleetai.com/careers (accessed 2026-06-07), careers page does not show a numeric open-role count
- has_researchers: yes [reported], source: https://www.fleetai.com/about (accessed 2026-06-07), team described as including people with prior research roles at Anthropic, xAI, Meta Superintelligence, Essential AI, Contextual AI, etc.
- researcher_count: unknown [unknown]
- researcher_backgrounds: Team self-describes prior experience at Anthropic, xAI, Meta Superintelligence, Essential AI, Contextual AI, Mercor, Docker, Citadel, Jane Street, and Cruise; Founder/CEO Nicolai (Nic) Ouporov: ex-founding engineer at Respell (acquired by Salesforce, Jan 2024); prior research at Stanford and Columbia per personal site [reported], source: https://www.fleetai.com/about (accessed 2026-06-07); https://www.nicolas.info/ (accessed 2026-06-07), backgrounds are self-described and not independently verified per person
- published_papers_or_benchmarks: 'Harbor', open-source framework for agent evaluations and creating/using RL environments (Apache-2.0; published under Fleet AI's GitHub org and a standalone harbor-framework repo) [reported], source: https://github.com/fleet-ai (accessed 2026-06-07); https://github.com/harbor-framework/harbor (accessed 2026-06-07); https://sacra.com/c/fleet/ (accessed 2026-06-07)
- total_raised: ~$15M disclosed (seed); a further round of at least $50M was reported in negotiation (~April 2026) but not confirmed closed [reported], source: https://sacra.com/c/fleet/ (accessed 2026-06-07); https://www.kucoin.com/news/flash/ai-training-firm-fleet-eyes-750m-valuation-amid-60x-revenue-surge (accessed 2026-06-07)
- last_round: Reported in talks (not confirmed closed): at least $50M at ~$750M post-money valuation, with Bain Capital Ventures reported as prospective lead, ~April 2026. Prior disclosed: ~$15M seed. [reported], source: https://www.theinformation.com/newsletters/ai-agenda/reinforcement-learning-gym-startup-buoyed-labs-appetite-training-data-reaches-750-million-valuation (accessed 2026-06-07); https://www.kucoin.com/news/flash/ai-training-firm-fleet-eyes-750m-valuation-amid-60x-revenue-surge (accessed 2026-06-07)
- notable_investors: Sequoia Capital; Menlo Ventures; SV Angel; Bain Capital Ventures (reported prospective lead of an in-talks round; not confirmed closed) [reported], source: https://www.fleetai.com/about (accessed 2026-06-07), lists Sequoia, Menlo, SV Angel; https://www.kucoin.com/news/flash/ai-training-firm-fleet-eyes-750m-valuation-amid-60x-revenue-surge (accessed 2026-06-07), BCV reported as prospective lead
- valuation: ~$750M reported for an in-talks round (~April 2026, not confirmed closed); prior seed valuation reported under $100M [reported], source: https://www.kucoin.com/news/flash/ai-training-firm-fleet-eyes-750m-valuation-amid-60x-revenue-surge (accessed 2026-06-07); https://www.theinformation.com/newsletters/ai-agenda/reinforcement-learning-gym-startup-buoyed-labs-appetite-training-data-reaches-750-million-valuation (accessed 2026-06-07)
- revenue_signals: Reported ~$60M annualized run-rate (~April 2026, computed as latest quarter x4), up from ~$1M annualized end-2025 [reported], source: https://sacra.com/c/fleet/ (accessed 2026-06-07); https://www.kucoin.com/news/flash/ai-training-firm-fleet-eyes-750m-valuation-amid-60x-revenue-surge (accessed 2026-06-07)
- soc2: unknown [unknown], source: No security/trust page found on fleetai.com (https://www.fleetai.com/security returned 404, accessed 2026-06-07); SOC 2 search results referred to an unrelated company (fleetdm.com)
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: https://www.fleetai.com/security (accessed 2026-06-07), returned 404; a status page exists but no trust/security page found
- what_they_sell: environments [confirmed], source: https://www.fleetai.com/about (accessed 2026-06-07); https://sacra.com/c/fleet/ (accessed 2026-06-07)
- open_source: yes [confirmed], source: https://github.com/fleet-ai (accessed 2026-06-07), publishes fleet-sdk (Apache-2.0), zeroboot (Apache-2.0), harbor/harbor-train (Apache-2.0), and other repos
- license: Apache-2.0 (for published OSS repos such as fleet-sdk, zeroboot, harbor); core hosted product not open source [confirmed], source: https://github.com/fleet-ai (accessed 2026-06-07)
- deployment_model: managed-hosted (platform API + Python SDK); some tooling is self-hostable via OSS repos [estimated], source: https://sacra.com/c/fleet/ (accessed 2026-06-07); https://github.com/fleet-ai (accessed 2026-06-07), fleet-sdk and platform API; explicit deployment model not stated
- maturity: GA [estimated], source: https://sacra.com/c/fleet/ (accessed 2026-06-07), reported paying labs/enterprises and a published SDK/API imply commercial availability; vendor does not use a GA label
- notable_customers: unknown [unknown], source: No specific Fleet AI customer is named or third-party-verified. Press/profiles describe frontier labs (OpenAI, Anthropic, Meta, Google) and financial-services/insurance enterprises only as the buyer CATEGORY for RL-environment vendors, not as confirmed Fleet customers. https://sacra.com/c/fleet/ (accessed 2026-06-07); https://sapphireventures.com/blog/reinforcement-learning-environments-ai-agents/ (accessed 2026-06-07)
- sources:
  - https://www.fleetai.com/ (accessed 2026-06-07)
  - https://www.fleetai.com/about (accessed 2026-06-07)
  - https://www.fleetai.com/careers (accessed 2026-06-07)
  - https://www.fleetai.com/security (accessed 2026-06-07)
  - https://sacra.com/c/fleet/ (accessed 2026-06-07)
  - https://www.kucoin.com/news/flash/ai-training-firm-fleet-eyes-750m-valuation-amid-60x-revenue-surge (accessed 2026-06-07)
  - https://www.theinformation.com/newsletters/ai-agenda/reinforcement-learning-gym-startup-buoyed-labs-appetite-training-data-reaches-750-million-valuation (accessed 2026-06-07)
  - https://www.nicolas.info/ (accessed 2026-06-07)
  - https://www.linkedin.com/company/fleet-so (accessed 2026-06-07)
  - https://rocketreach.co/fleet-ai-management_b6f95050c628d05e (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/fleet-6338 (accessed 2026-06-07)
  - https://sapphireventures.com/blog/reinforcement-learning-environments-ai-agents/ (accessed 2026-06-07)
  - https://newsletter.semianalysis.com/p/rl-environments-and-rl-for-science (accessed 2026-06-07)

## Datacurve, rank #7
- slug: datacurve
- segment: Commercial vendors
- website: https://datacurve.ai/
- focus_areas: Coding, Private Codebases
- positioning: Datacurve is a YC W24 commercial data vendor that supplies expert-curated frontier coding data, RLHF traces, and repository-wide reinforcement learning environments (with unit-test verifiers) to foundation model labs, sourced via its Shipd bounty platform of vetted software engineers. It also publishes DeepSWE, a long-horizon agentic coding benchmark.
- best_fit: Frontier/foundation model labs needing expert-sourced coding SFT/RLHF data and code-execution RL environments with verifiable rewards (code execution, tight loops).
- overall_confidence: medium
- founded_year: 2024 [confirmed], source: https://www.ycombinator.com/companies/datacurve (accessed 2026-06-07), Winter 2024 batch, founded 2024
- status: active [confirmed], source: https://datacurve.ai/ (accessed 2026-06-07); https://techcrunch.com/2025/10/09/datacurve-raises-15-million-to-take-on-scaleai/ (accessed 2026-06-07)
- hq_location: San Francisco, USA [confirmed], source: https://www.ycombinator.com/companies/datacurve (accessed 2026-06-07); https://www.linkedin.com/company/datacurveai (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: no (San Francisco office-based; careers page lists in-office meals and commuter benefits) [estimated], source: https://datacurve.ai/careers (accessed 2026-06-07)
- current_headcount: approx 36 (LinkedIn 'Discover all 36 employees', size band 11-50) as of 2026-06-07 [reported], source: https://www.linkedin.com/company/datacurveai (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/datacurveai (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: 3 [confirmed], source: https://datacurve.ai/careers (accessed 2026-06-07), Software Engineer, Research Engineer, Growth/Operations
- has_researchers: yes [reported], source: https://datacurve.ai/careers (accessed 2026-06-07), Research Engineer role; co-founders have ML/AI research backgrounds
- researcher_count: unknown [unknown]
- researcher_backgrounds: Serena Ge (co-founder/CEO): worked on LLM reasoning during a co-op at Cohere; University of Waterloo CS; Forbes 30 Under 30; Charley Lee (co-founder): University of Waterloo CS; AI research background [reported], source: https://uwaterloo.ca/computer-science/news/cs-led-startup-secures-177m-transform-ai-training-data (accessed 2026-06-07)
- published_papers_or_benchmarks: DeepSWE, long-horizon agentic coding benchmark, 113 tasks across TypeScript/Go/Python/JavaScript/Rust with isolated test environments and program-based verifiers (github.com/datacurve-ai/deep-swe). Distinct from the Together AI/Agentica 'DeepSWE' coding agent of the same name. [confirmed], source: https://github.com/datacurve-ai/deep-swe (accessed 2026-06-07)
- total_raised: $17.7M ($15M Series A + $2.7M seed) [confirmed], source: https://techcrunch.com/2025/10/09/datacurve-raises-15-million-to-take-on-scaleai/ (accessed 2026-06-07); https://uwaterloo.ca/computer-science/news/cs-led-startup-secures-177m-transform-ai-training-data (accessed 2026-06-07)
- last_round: Series A, $15M, October 2025 [confirmed], source: https://techcrunch.com/2025/10/09/datacurve-raises-15-million-to-take-on-scaleai/ (accessed 2026-06-07)
- notable_investors: Chemistry (Mark Goldberg, lead Series A); Y Combinator; Balaji Srinivasan (seed); angel investors who are employees of DeepMind, Vercel, Anthropic and OpenAI (individuals, not the companies) [reported], source: https://techcrunch.com/2025/10/09/datacurve-raises-15-million-to-take-on-scaleai/ (accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown (over $1M paid out in bounties to contributors, a payout figure, not revenue) [unknown], source: https://techcrunch.com/2025/10/09/datacurve-raises-15-million-to-take-on-scaleai/ (accessed 2026-06-07)
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: mixed [confirmed], source: https://datacurve.ai/ (accessed 2026-06-07); https://techcrunch.com/2025/10/09/datacurve-raises-15-million-to-take-on-scaleai/ (accessed 2026-06-07)
- open_source: no (company products are commercial/proprietary; only the DeepSWE benchmark repo is published publicly) [reported], source: https://github.com/datacurve-ai/deep-swe (accessed 2026-06-07); https://datacurve.ai/ (accessed 2026-06-07)
- license: unknown (DeepSWE repo has no license file shown as of access date) [unknown], source: https://github.com/datacurve-ai/deep-swe (accessed 2026-06-07), no license specified
- deployment_model: managed-hosted (data delivered as a service; private model endpoints spun up for RLHF traces) [reported], source: https://sacra.com/c/datacurve/ (accessed 2026-06-07)
- maturity: GA [estimated], source: https://datacurve.ai/ (accessed 2026-06-07), commercially operating with paying labs and active Shipd bounty platform
- notable_customers: unknown [unknown], source: Vendor and press describe 'frontier AI labs / foundation model labs' and 'multimillion-dollar contracts with leading AI labs' but name no specific customer; not verifiable
- sources:
  - https://datacurve.ai/ (accessed 2026-06-07)
  - https://datacurve.ai/careers (accessed 2026-06-07)
  - https://www.ycombinator.com/companies/datacurve (accessed 2026-06-07)
  - https://www.linkedin.com/company/datacurveai (accessed 2026-06-07)
  - https://techcrunch.com/2025/10/09/datacurve-raises-15-million-to-take-on-scaleai/ (accessed 2026-06-07)
  - https://sacra.com/c/datacurve/ (accessed 2026-06-07)
  - https://github.com/datacurve-ai/deep-swe (accessed 2026-06-07)
  - https://api.github.com/repos/datacurve-ai/deep-swe (accessed 2026-06-07)
  - https://uwaterloo.ca/computer-science/news/cs-led-startup-secures-177m-transform-ai-training-data (accessed 2026-06-07)
  - https://www.chemistry.vc/post/staying-ahead-of-the-curve (accessed 2026-06-07)
  - https://www.menlotimes.com/post/datacurve-is-taking-on-scale-ai-building-frontier-coding-data-for-foundation-model-labs (accessed 2026-06-07)

## Proximal, rank #8
- slug: proximal
- segment: Commercial vendors
- website: https://www.proximal.ai
- focus_areas: Coding, Long-Horizon, Private Codebases
- positioning: Proximal is a San Francisco-based (with a Bangalore presence) research lab for coding data, building high-fidelity, long-horizon reinforcement learning environments grounded in real codebases to train and evaluate frontier coding agents. It emphasizes scalable, software-driven data engines over human contractors, and research into reward-hacking detection and 'fuzzy verifiers' that score code quality beyond functional correctness.
- best_fit: Frontier labs or AI startups needing long-horizon, real-codebase RL environments and quality-aware (fuzzy) verifiers to post-train coding agents.
- overall_confidence: medium
- founded_year: 2026 [reported], source: https://www.proximal.ai/blog/proximal (announced 2026-02-18; accessed 2026-06-07)
- status: active [confirmed], source: https://www.proximal.ai/ (accessed 2026-06-07)
- hq_location: San Francisco, CA, USA [confirmed], source: https://www.proximal.ai/blog/proximal (San Francisco); https://www.proximal.ai/careers (accessed 2026-06-07)
- other_locations: Bangalore, India [reported], source: https://www.proximal.ai/careers (accessed 2026-06-07)
- distributed_remote: no [reported], source: https://www.proximal.ai/careers (emphasizes in-person collaboration in SF and Bangalore; accessed 2026-06-07)
- current_headcount: 11-50 band (LinkedIn); '~25' is an unverified estimate [estimated], source: https://www.linkedin.com/company/proximalhq (public snippet shows 11-50; accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/proximalhq (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: 3 [reported], source: https://www.proximal.ai/careers (3 roles per draft snapshot; titles not independently re-confirmed; accessed 2026-06-07)
- has_researchers: yes [confirmed], source: https://www.proximal.ai/blog/proximal (team of engineers and researchers; members published at leading conferences; accessed 2026-06-07)
- researcher_count: unknown [unknown]
- researcher_backgrounds: Justus Mattern (co-founder) - led RL research & data at Prime Intellect, core contributor to its RL training framework (Intellect-2); co-founded Revideo (YC S23); early engineer at Dynamo AI (confirmed via justusmattern.com); Calvin Chen (co-founder) - works on Proximal; part of a 'second-time exited' founding team (specifics of any prior company exit, ARR or sale amount NOT corroborated by his own site); Navid Pour (co-founder) - prior Cursor experience per founder posts ('early engineers from Cursor'); specific 'second founding engineer / Cursor tab' and 'Fetchr' claims NOT corroborated; Founding team alumni from Cursor, Prime Intellect, Browserbase and Jane Street; members with published papers at leading research conferences [reported], source: https://www.justusmattern.com/ ; https://www.calvinjaychen.com/ ; https://www.linkedin.com/posts/imstusmith_excited-to-finally-share-that-scribble-ventures-activity-7430007099004432384-cqbR (accessed 2026-06-07)
- published_papers_or_benchmarks: FrontierSWE - ultra long-horizon coding agent benchmark (implementation, performance engineering, ML research) - https://www.frontierswe.com ; https://github.com/Proximal-Labs/frontier-swe [confirmed], source: https://www.frontierswe.com ; https://github.com/Proximal-Labs/frontier-swe (accessed 2026-06-07)
- total_raised: unknown [unknown]
- last_round: Early/seed-stage round (stage label inferred; amount undisclosed); led by Scribble Ventures [reported], source: https://www.linkedin.com/posts/imstusmith_excited-to-finally-share-that-scribble-ventures-activity-7430007099004432384-cqbR ; https://www.proximal.ai/blog/proximal (accessed 2026-06-07)
- notable_investors: Scribble Ventures (lead); Angels from OpenAI, Anthropic, Thinking Machines, Google DeepMind, xAI, Meta Superintelligence, Cursor and Cognition (per founders' own statements; not independently verified) [reported], source: https://www.calvinjaychen.com/ (founder site lists these angel affiliations); https://www.linkedin.com/posts/imstusmith_excited-to-finally-share-that-scribble-ventures-activity-7430007099004432384-cqbR (accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown], source: No security/trust page found; https://www.proximal.ai/security returned 404 (accessed 2026-06-07)
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: https://www.proximal.ai/security returned 404 (accessed 2026-06-07)
- what_they_sell: environments [confirmed], source: https://www.proximal.ai/blog/proximal ; https://www.proximal.ai/blog/our-problems (high-fidelity, long-horizon RL environments / coding data engine; accessed 2026-06-07)
- open_source: yes [confirmed], source: https://github.com/Proximal-Labs/frontier-swe (FrontierSWE benchmark, 127 stars; accessed 2026-06-07)
- license: unknown [unknown], source: https://github.com/Proximal-Labs/frontier-swe (license not shown in fetched content; accessed 2026-06-07)
- deployment_model: unknown [unknown]
- maturity: unknown [unknown]
- notable_customers: unknown [unknown], source: Company states it works with frontier labs / AI startups but names no specific customers publicly; no third-party customer confirmation found (accessed 2026-06-07)
- sources:
  - https://www.proximal.ai/ (accessed 2026-06-07)
  - https://www.proximal.ai/blog/proximal (accessed 2026-06-07)
  - https://www.proximal.ai/blog/our-problems (accessed 2026-06-07)
  - https://www.proximal.ai/careers (accessed 2026-06-07)
  - https://www.linkedin.com/company/proximalhq (accessed 2026-06-07)
  - https://www.linkedin.com/posts/imstusmith_excited-to-finally-share-that-scribble-ventures-activity-7430007099004432384-cqbR (accessed 2026-06-07)
  - https://www.linkedin.com/posts/justus-mattern-a04230184_incredibly-excited-to-introduce-proximal-activity-7429982692999438336-Bsdr (accessed 2026-06-07)
  - https://www.justusmattern.com/ (accessed 2026-06-07)
  - https://www.frontierswe.com (accessed 2026-06-07)
  - https://github.com/Proximal-Labs/frontier-swe (accessed 2026-06-07)
  - https://www.proximal.ai/security (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/proximal (accessed 2026-06-07)

## Gray Swan AI, rank #9
- slug: gray-swan-ai
- segment: Commercial vendors
- website: https://www.grayswan.ai/
- focus_areas: unknown
- positioning: Gray Swan AI is a Pittsburgh-based AI security company spun out of Carnegie Mellon, offering adversarial red-teaming and runtime protection for AI models and agents via three products: Arena (a crowdsourced adversarial red-teaming network of 15,000+ researchers), Shade (automated red-teaming/pressure-testing), and Cygnal (runtime input/output guardrails). It positions itself as a security/evaluation partner to frontier labs and enterprises rather than a general RL-environment vendor.
- best_fit: Buyers needing adversarial evaluation, red-teaming arenas, and runtime guardrails for frontier or enterprise LLM/agent deployments.
- overall_confidence: medium
- founded_year: 2023 or 2024 (conflicting: LinkedIn lists 2023; Tracxn lists 2024; public product launch July 16, 2024) [reported], source: https://www.linkedin.com/company/grayswanai (public snippet, accessed 2026-06-07); https://tracxn.com/d/companies/gray-swan-ai/__nZCNR23H086-Z-r6gED-nlgrD6otsq465-kAbWKigfY (accessed 2026-06-07); https://www.grayswan.ai/blog/gray-swan-launch (accessed 2026-06-07)
- status: active [confirmed], source: https://www.grayswan.ai/news/gray-swan-announces-series-a (accessed 2026-06-07)
- hq_location: Pittsburgh, Pennsylvania, USA [reported], source: https://www.linkedin.com/company/grayswanai (public snippet, accessed 2026-06-07); https://www.finsmes.com/2026/06/gray-swan-raises-40m-in-series-a-funding.html (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: yes (careers page states flexible work arrangements) [reported], source: https://www.grayswan.ai/careers (accessed 2026-06-07)
- current_headcount: ~29-75 (LinkedIn shows ~75 employees listed; Tracxn reports 59 as of 2026-04-30; PitchBook reports 29) - figure uncertain, sources diverge [estimated], source: https://www.linkedin.com/company/grayswanai (accessed 2026-06-07); https://tracxn.com/d/companies/gray-swan-ai/__nZCNR23H086-Z-r6gED-nlgrD6otsq465-kAbWKigfY (accessed 2026-06-07); https://pitchbook.com/profiles/company/633269-80 (accessed 2026-06-07)
- headcount_band: 11-50 [estimated], source: https://pitchbook.com/profiles/company/633269-80 (accessed 2026-06-07); https://tracxn.com/d/companies/gray-swan-ai/__nZCNR23H086-Z-r6gED-nlgrD6otsq465-kAbWKigfY (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown (careers page advertises ML Engineer roles; exact count not enumerated) [unknown], source: https://www.grayswan.ai/careers (accessed 2026-06-07)
- has_researchers: yes [confirmed], source: https://www.grayswan.ai/about (accessed 2026-06-07)
- researcher_count: unknown (research team referenced; exact count not published) [unknown], source: https://www.grayswan.ai/about (accessed 2026-06-07)
- researcher_backgrounds: Zico Kolter (Co-founder, Chief Scientist) - CMU professor, AI safety/robustness researcher, OpenAI board member; Matt Fredrikson (Co-founder, CEO) - CMU faculty, adversarial ML researcher; Founding team of AI safety/security researchers from Carnegie Mellon University; Andy Zou - listed as co-founder by Tracxn only; not shown on the company's own about/team page (unconfirmed) [reported], source: https://www.grayswan.ai/about (accessed 2026-06-07); https://tracxn.com/d/companies/gray-swan-ai/__nZCNR23H086-Z-r6gED-nlgrD6otsq465-kAbWKigfY (accessed 2026-06-07)
- published_papers_or_benchmarks: Research cited in 11 frontier model system cards (Anthropic Claude family, OpenAI GPT-5/o1/o3-mini, Meta Muse Spark) - per vendor; UK AISI x Gray Swan Agent Red-Teaming Challenge (https://www.grayswan.ai/news/uk-aisi-x-gray-swan-agent-red-teaming-challenge-results-snapshot); NIST CAISI blog: Insights into AI Agent Security from a Large-Scale Red-Teaming Competition (https://www.nist.gov/blogs/caisi-research-blog/insights-ai-agent-security-large-scale-red-teaming-competition) [reported], source: https://www.grayswan.ai/about (accessed 2026-06-07); https://www.nist.gov/blogs/caisi-research-blog/insights-ai-agent-security-large-scale-red-teaming-competition (accessed 2026-06-07)
- total_raised: $40M disclosed (Series A $40M; any prior seed amount not publicly disclosed) [reported], source: https://www.grayswan.ai/news/gray-swan-announces-series-a (accessed 2026-06-07); https://www.finsmes.com/2026/06/gray-swan-raises-40m-in-series-a-funding.html (accessed 2026-06-07)
- last_round: Series A, $40M, May 28, 2026 [confirmed], source: https://www.grayswan.ai/news/gray-swan-announces-series-a (accessed 2026-06-07); https://www.finsmes.com/2026/06/gray-swan-raises-40m-in-series-a-funding.html (accessed 2026-06-07)
- notable_investors: Wing Venture Capital (co-lead); Madrona (co-lead); Obvious Ventures; Snowflake Ventures; Hudson River Trading; Samsung Next; Magarac Venture Partners (existing) [confirmed], source: https://www.grayswan.ai/news/gray-swan-announces-series-a (accessed 2026-06-07); https://www.finsmes.com/2026/06/gray-swan-raises-40m-in-series-a-funding.html (accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: Type II [reported], source: https://trust.grayswan.ai (accessed 2026-06-07)
- other_certifications: Cyber Essentials [reported], source: https://trust.grayswan.ai (accessed 2026-06-07)
- security_page: https://trust.grayswan.ai [confirmed], source: https://www.grayswan.ai/ (accessed 2026-06-07)
- what_they_sell: mixed (adversarial red-teaming/evals + runtime security infra; Arena crowdsourced red-teaming generates attack-trajectory data) [confirmed], source: https://www.grayswan.ai/about (accessed 2026-06-07); https://www.grayswan.ai/ (accessed 2026-06-07)
- open_source: no [estimated], source: https://www.grayswan.ai/ (accessed 2026-06-07)
- license: unknown [unknown]
- deployment_model: managed-hosted / API (SaaS: Cygnal runtime protection, Shade red-teaming, Arena hosted competition) [reported], source: https://www.grayswan.ai/ (accessed 2026-06-07)
- maturity: GA [reported], source: https://www.grayswan.ai/news/gray-swan-announces-series-a (accessed 2026-06-07)
- notable_customers: Anthropic (verified, frontier-lab tie); OpenAI (verified, frontier-lab tie); Meta (verified, frontier-lab tie); Google DeepMind (self-claimed, frontier-lab tie); xAI (self-claimed, frontier-lab tie); Amazon (self-claimed); Snowflake (self-claimed); ByteDance (self-claimed); ElevenLabs (self-claimed); Intercom (self-claimed); Deloitte (self-claimed); UK AI Security Institute (AISI) (verified); Anaconda (self-claimed); OpenHands (self-claimed); AIUC (self-claimed) [reported], source: https://www.grayswan.ai/ logos (self-claimed, accessed 2026-06-07); Anthropic/OpenAI/Meta named in Series A press release and cited in 11 frontier model system cards per https://www.grayswan.ai/news/gray-swan-announces-series-a and https://www.grayswan.ai/about (accessed 2026-06-07); UK AISI joint challenge corroborated by NIST CAISI per https://www.nist.gov/blogs/caisi-research-blog/insights-ai-agent-security-large-scale-red-teaming-competition (accessed 2026-06-07)
- sources:
  - https://www.grayswan.ai/ (accessed 2026-06-07)
  - https://www.grayswan.ai/about (accessed 2026-06-07)
  - https://www.grayswan.ai/news/gray-swan-announces-series-a (accessed 2026-06-07)
  - https://www.grayswan.ai/careers (accessed 2026-06-07)
  - https://trust.grayswan.ai (accessed 2026-06-07)
  - https://www.linkedin.com/company/grayswanai (accessed 2026-06-07)
  - https://tracxn.com/d/companies/gray-swan-ai/__nZCNR23H086-Z-r6gED-nlgrD6otsq465-kAbWKigfY (accessed 2026-06-07)
  - https://www.finsmes.com/2026/06/gray-swan-raises-40m-in-series-a-funding.html (accessed 2026-06-07)
  - https://technical.ly/entrepreneurship/gray-swan-ai-security-40m-series-a/ (accessed 2026-06-07)
  - https://natlawreview.com/press-releases/gray-swan-ai-security-company-trusted-every-major-frontier-lab-raises-40m (accessed 2026-06-07)
  - https://www.nist.gov/blogs/caisi-research-blog/insights-ai-agent-security-large-scale-red-teaming-competition (accessed 2026-06-07)
  - https://www.grayswan.ai/news/uk-aisi-x-gray-swan-agent-red-teaming-challenge-results-snapshot (accessed 2026-06-07)

## Veris AI, rank #10
- slug: veris-ai
- segment: Commercial vendors
- website: https://veris.ai
- focus_areas: Enterprise Workflows
- positioning: Veris AI sells a high-fidelity simulation platform plus a production runtime that let enterprises train, evaluate, and govern AI agents against mocked enterprise tools before and during production, with support for reinforcement learning / fine-tuning pipelines. It positions itself as the enterprise 'environment layer' that agent builders lack.
- best_fit: Enterprise teams building agents for messy multi-step internal workflows who need safe simulated environments to evaluate, train (RL/RFT), and govern those agents before production.
- overall_confidence: medium
- founded_year: 2025 [reported], source: https://www.linkedin.com/company/veris-ai public snippet (founded 2025); https://www.businesswire.com/news/home/20250603868539/en/ (emerged from stealth June 2025) (accessed 2026-06-07)
- status: active [confirmed], source: https://veris.ai/about; https://veris.ai/ (accessed 2026-06-07)
- hq_location: San Francisco, CA, USA [reported], source: https://www.linkedin.com/company/veris-ai public snippet (HQ San Francisco) (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: 1-10 (approx 9) as of 2026-06-07 [reported], source: https://www.linkedin.com/company/veris-ai public snippet (9 employees / 1-10 band); https://veris.ai/about (named team members) (accessed 2026-06-07)
- headcount_band: 1-10 [reported], source: https://www.linkedin.com/company/veris-ai public snippet (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: Careers links to external jobs board; at least one role (Member of Technical Staff, SF) seen on LinkedIn Jobs but no reliable total count (accessed 2026-06-07)
- has_researchers: yes [confirmed], source: https://veris.ai/about (Applied Research Engineer / Senior Applied Research Engineer roles); founders hold PhDs (accessed 2026-06-07)
- researcher_count: ~2 applied research engineers (counted from team page) plus two co-founders with research/PhD backgrounds [estimated], source: https://veris.ai/about (applied research engineer roles listed) (accessed 2026-06-07)
- researcher_backgrounds: CEO Mehdi Jamei: PhD EECS UC Berkeley; previously led agentic AI at System and Workmate; CTO Andi Partovi: PhD (brain-computer interfaces) University of Melbourne; ex-Solutions Architect at Google; ex-founder/CTO KeyLead Health [reported], source: https://www.businesswire.com/news/home/20250603868539/en/; https://pulse2.com/veris-ai-8-5-million-raised-for-training-ai-agents/; https://www.linkedin.com/in/mehdijamei/; https://www.linkedin.com/in/andi-partovi/ (accessed 2026-06-07)
- published_papers_or_benchmarks: Technical Report: How Reinforcement Fine-tuning Trains Enterprise-Grade Domain-specific Agents (Dec 2025) - https://veris.ai/blog/technical-report-reinforcement-learning-fine-tuning-for-enterprise-ai-agents [reported], source: https://veris.ai/blog/technical-report-reinforcement-learning-fine-tuning-for-enterprise-ai-agents (vendor blog technical report; not peer-reviewed) (accessed 2026-06-07)
- total_raised: $8.5M [confirmed], source: https://www.businesswire.com/news/home/20250603868539/en/; https://www.finsmes.com/2025/06/veris-ai-raises-8-5m-in-seed-funding.html; https://pulse2.com/veris-ai-8-5-million-raised-for-training-ai-agents/; https://www.citybiz.co/article/701730/ (accessed 2026-06-07)
- last_round: Seed, $8.5M, June 2025 [confirmed], source: https://www.businesswire.com/news/home/20250603868539/en/ (stealth emergence June 2025); https://pulse2.com/veris-ai-8-5-million-raised-for-training-ai-agents/ (round stage: Seed) (accessed 2026-06-07)
- notable_investors: Decibel Ventures (lead); Acrew Capital (lead); The House Fund; Ian Livingstone; Idris Mokhtarzada (Rocket Money); Dorothy Chang [confirmed], source: https://www.businesswire.com/news/home/20250603868539/en/; https://pulse2.com/veris-ai-8-5-million-raised-for-training-ai-agents/; https://www.citybiz.co/article/701762/; https://www.citybiz.co/article/701797/ (accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: claimed-unverified [reported], source: https://veris.ai/faqs (vendor states 'Veris AI is SOC 2 Type 2 Compliant'; no third-party trust page, auditor, or registry confirmation found) (accessed 2026-06-07)
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: No dedicated /security or /trust page found; SOC 2 and security controls described on FAQ page only (accessed 2026-06-07)
- what_they_sell: environments [confirmed], source: https://veris.ai/faqs (Simulation Platform + Veris Runtime); https://www.businesswire.com/news/home/20250603868539/en/ (high-fidelity simulated environments for training/testing agents) (accessed 2026-06-07)
- open_source: no [reported], source: https://veris.ai (no public repos/OSS offering found; commercial proprietary platform) (accessed 2026-06-07)
- license: unknown [unknown]
- deployment_model: managed-hosted (Veris Cloud), self-hosted (customer VPC on AWS/GCP/Azure), and on-prem [confirmed], source: https://veris.ai/faqs ('supports deployment on your own cloud (AWS, GCP, Azure) or on-prem'; Veris Cloud managed option) (accessed 2026-06-07)
- maturity: GA [reported], source: https://veris.ai/faqs (no beta designation; standard onboarding/deployment described; waitlist opened at launch per BusinessWire) (accessed 2026-06-07)
- notable_customers: Consumer fintech company (unnamed) - compliant chatbots (self-claimed); HR tech / executive-assistant agent company (unnamed) (self-claimed); Manufacturer - supply chain agent (unnamed) (self-claimed) [reported], source: https://www.alleywatch.com/2025/06/veris-ai-enterprise-ai-agents-agentic-simulation-based-training-platform-mehdi-jamei/ (customers described only by category, none named; no frontier-lab ties found) (accessed 2026-06-07)
- sources:
  - https://veris.ai/about (accessed 2026-06-07)
  - https://veris.ai/faqs (accessed 2026-06-07)
  - https://veris.ai/ (accessed 2026-06-07)
  - https://veris.ai/blog/technical-report-reinforcement-learning-fine-tuning-for-enterprise-ai-agents (accessed 2026-06-07)
  - https://www.alleywatch.com/2025/06/veris-ai-enterprise-ai-agents-agentic-simulation-based-training-platform-mehdi-jamei/ (accessed 2026-06-07)
  - https://www.businesswire.com/news/home/20250603868539/en/ (accessed 2026-06-07)
  - https://www.citybiz.co/article/701797/ (accessed 2026-06-07)
  - https://www.linkedin.com/company/veris-ai (accessed 2026-06-07)
  - https://mjamei.github.io/ (accessed 2026-06-07)
  - https://www.linkedin.com/in/andi-partovi/ (accessed 2026-06-07)
  - https://qconsf.com/speakers/andipartovi (accessed 2026-06-07)
  - https://www.decibel.vc/articles/veris-ai-why-the-environment-is-everything-for-autonomous-ai-agents (accessed 2026-06-07)

## Chakra Labs, rank #11
- slug: chakra-labs
- segment: Commercial vendors
- website: https://www.chakra.dev/
- focus_areas: Computer Use
- positioning: Chakra Labs runs Dojo, an open/collaborative reinforcement-learning environment hub for computer-use agents, offering deterministic, frame-accurate clones of production software plus human computer-use trajectory datasets, with native support for the Harbor, Verifiers and Verl RL frameworks. It positions itself as bringing frontier-lab-grade CUA training infrastructure to the broader research community.
- best_fit: Teams training or evaluating computer-use / GUI agents that need ready-made, deterministic clones of production software environments plus human trajectory data.
- overall_confidence: medium
- founded_year: 2024 [reported], source: https://www.alleywatch.com/2026/01/the-alleywatch-startup-daily-funding-report-1-26-2026/ (accessed 2026-06-07), 'founded by Alexander Fung and Nirmal Krishnan in 2024'
- status: active [confirmed], source: https://www.chakra.dev/ (accessed 2026-06-07); GitHub org repos with pushes through 2026-06-05 https://github.com/chakra-network (accessed 2026-06-07)
- hq_location: Brooklyn, New York, USA [reported], source: Search snippets / Crunchbase listing for Chakra Labs (Crunchbase fetch returned HTTP 403; corroborated via search) (accessed 2026-06-07); founders listed as based in New York, NY
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: ~14 [reported], source: https://www.linkedin.com/company/chakra-labs (public snippet, accessed 2026-06-07), single source; LinkedIn size band still listed as 2-10
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/chakra-labs (public snippet, accessed 2026-06-07), LinkedIn shows a '2-10' size band but ~14 associated employees; band placed at 11-50 on the higher employee count. Conflicting signals; treat as approximate.
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: Careers at jobs.ashbyhq.com/chakra-labs (accessed 2026-06-07), listings not extractable from public snippet
- has_researchers: yes [reported], source: https://www.chakra.dev/ (accessed 2026-06-07), self-described 'applied research team pushing the boundaries of agents'; publishes research/CUA market analyses
- researcher_count: unknown [unknown]
- researcher_backgrounds: Alexander Fung (co-founder), ex-Palantir, Snap/Snapchat, Fin; Computer Science, University of Waterloo (per LinkedIn/search snippets); Nirmal Krishnan (co-founder), Computer Science & ML, Johns Hopkins; prior data/early-stage startup experience (per LinkedIn/search snippets) [reported], source: Search snippets from LinkedIn profiles (linkedin.com/in/alexfung, linkedin.com/in/nirmal-krishnan) and https://www.chakra.dev/publications/product-launch-dojo (accessed 2026-06-07). Exact titles (CTO/CEO) not independently confirmed.
- published_papers_or_benchmarks: GLADOS-1, described as 'the first computer-use (CUA) model post-trained using collective, crowd-sourced trajectories' (GitHub repo, Apache-2.0), a released model/repo, not a peer-reviewed paper; 'Computer Use Agents' Part I & II, market map / ecosystem analysis posts (Chakra Labs on X, @chakra_ai); Dojo product launch write-up on chakra.dev [reported], source: https://github.com/chakra-network and https://x.com/chakra_ai (accessed 2026-06-07). Note: these are product/blog/social artifacts, not formal academic papers or third-party benchmarks.
- total_raised: $10.1M (disclosed via SEC filing, reported 2026-01-26) [reported], source: https://www.alleywatch.com/2026/01/the-alleywatch-startup-daily-funding-report-1-26-2026/ (accessed 2026-06-07), single-source funding report based on SEC filing
- last_round: $10.1M (stage unspecified; SEC filing reported 2026-01-26, ~50 investors) [reported], source: https://www.alleywatch.com/2026/01/the-alleywatch-startup-daily-funding-report-1-26-2026/ (accessed 2026-06-07)
- notable_investors: unknown [unknown], source: AlleyWatch cites ~50 investors per SEC filing but names none (accessed 2026-06-07). NOTE: do not confuse with same-named crypto/Bitcoin-restaking 'Chakra' (StarkWare/ABCDE), which is a different company.
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: chakra.dev/security returned 404 (accessed 2026-06-07)
- what_they_sell: environments [confirmed], source: https://trydojo.ai/, 'The RL Environment Hub for Computer Use Agents'; https://www.chakra.dev/, deterministic RL environments plus human computer-use trajectory datasets (2,500+ hrs trajectories, 10M screenshot/action pairs) (accessed 2026-06-07). Note: AlleyWatch frames the company as turning public web data into structured datasets, older/adjacent framing.
- open_source: yes [confirmed], source: https://github.com/chakra-network (accessed 2026-06-07), public repos GLADOS-1, harbor, marina, dojo-spas, software-agent-sdk
- license: Mixed: Apache-2.0 (GLADOS-1, harbor, marina, harbor-start-script); MIT (software-agent-sdk, cli-mcp-server); some repos (dojo-spas, verl-tools, servers) have no declared license [confirmed], source: https://github.com/chakra-network (accessed 2026-06-07)
- deployment_model: managed-hosted (shared platform / request access); native support for Harbor, Verifiers, and Verl RL frameworks [reported], source: https://trydojo.ai/, 'Native support for Harbor, Verifiers, and Verl'; access via request form (accessed 2026-06-07)
- maturity: private beta (request access) [estimated], source: https://trydojo.ai/, 'Request Access' gating; Dojo launched 2025-10-31 per https://www.chakra.dev/publications/product-launch-dojo (accessed 2026-06-07)
- notable_customers: unknown [unknown], source: Site references collaboration with unnamed 'leading research teams' (https://www.chakra.dev/, https://trydojo.ai/, accessed 2026-06-07), self-claimed, no named or verified customers
- sources:
  - https://trydojo.ai/ (accessed 2026-06-07)
  - https://www.chakra.dev/ (accessed 2026-06-07)
  - https://www.chakra.dev/publications/product-launch-dojo (accessed 2026-06-07)
  - https://github.com/chakra-network (accessed 2026-06-07)
  - https://www.linkedin.com/company/chakra-labs (accessed 2026-06-07)
  - https://www.alleywatch.com/2026/01/the-alleywatch-startup-daily-funding-report-1-26-2026/ (accessed 2026-06-07)
  - https://x.com/chakra_ai (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/chakra-labs (accessed 2026-06-07)
  - https://jobs.ashbyhq.com/chakra-labs (accessed 2026-06-07)

## Andon Labs, rank #12
- slug: andon-labs
- segment: Commercial vendors
- website: https://andonlabs.com
- focus_areas: Computer Use, Long-Horizon
- positioning: Andon Labs is a Y Combinator-backed (W24) startup, formerly Vectorview, building benchmarks and evaluations for AI agents' long-horizon coherence and safety (Vending-Bench, Butter-Bench, Blueprint-Bench) and operating real-world autonomous AI businesses. It is known for high-profile collaborations placing AI-run vending machines/stores in the offices of frontier labs Anthropic (Project Vend) and xAI (Grokbox).
- best_fit: Buyers wanting long-horizon agent coherence/safety benchmarks and real-world autonomous-operation stress tests, with a frontier-lab-adjacent, irreverent eval style.
- overall_confidence: medium
- founded_year: 2023 [reported], source: https://www.ycombinator.com/companies/andon-labs (accessed 2026-06-07); https://tracxn.com/d/companies/andonlabs (accessed 2026-06-07). Note: company was formerly named Vectorview and rebranded to Andon Labs around late 2024; predecessor Vectorview activity may predate 2023.
- status: active [confirmed], source: https://andonlabs.com/ (accessed 2026-06-07); https://www.anthropic.com/research/project-vend-2 (accessed 2026-06-07); https://fortune.com/2026/06/02/anthropic-office-vending-machine-ai-agents-vendo-andon-lukas-petersson/ (accessed 2026-06-07)
- hq_location: San Francisco, USA [reported], source: https://www.ycombinator.com/companies/andon-labs (accessed 2026-06-07); https://tracxn.com/d/companies/andonlabs (accessed 2026-06-07). Note: Swedish origins (formerly Vectorview, Bromma/Stockholm, Sweden); operates in both SF and Stockholm. Some databases list HQ as Bromma, Sweden.
- other_locations: Stockholm, Sweden (Andon Cafe; AI 'Mona'); San Francisco, USA (Andon Market retail store, Cow Hollow; AI 'Luna') [reported], source: https://www.linkedin.com/company/andonlabs (public snippet, accessed 2026-06-07); https://www.pymnts.com/artificial-intelligence-2/2026/andon-labs-handed-an-ai-a-cafe-and-business-boomed/ (accessed 2026-06-07); https://www.nbcnews.com/tech/innovation/ai-store-sf-san-francisco-bay-area-andon-labs-market-boss-rcna267013 (accessed 2026-06-07)
- distributed_remote: unknown [unknown]
- current_headcount: ~16 employees (as of 2026-04-30 per Tracxn); LinkedIn lists ~18 associated profiles; YC profile states 10 (likely stale) [reported], source: https://tracxn.com/d/companies/andonlabs (accessed 2026-06-07); https://www.linkedin.com/company/andonlabs (public snippet, accessed 2026-06-07); https://www.ycombinator.com/companies/andon-labs (accessed 2026-06-07)
- headcount_band: 11-50 [estimated], source: Inferred from Tracxn ~16 employees and LinkedIn ~18 profiles (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: https://andonlabs.com/join (careers page exists); postings seen for Member of Technical Staff, Founders Associate (SF), Operations Generalist Intern, but no reliable public count as of 2026-06-07
- has_researchers: yes [confirmed], source: https://arxiv.org/abs/2510.21860 (Butter-Bench paper, accessed 2026-06-07), authored by Andon Labs team; company publishes benchmark research.
- researcher_count: ~7 (counted as authors on the Butter-Bench paper; not a full team census) [estimated], source: https://arxiv.org/abs/2510.21860 (accessed 2026-06-07): authors include Callum Sharrock, Lukas Petersson, Hanna Petersson, Axel Backlund, Axel Wennstrom, Kristoffer Nordstrom, Elias Aronsson
- researcher_backgrounds: Lukas Petersson (CEO, co-founder), previously co-founded Vectorview; Axel Backlund (CTO, co-founder); Emil Froberg, co-founder (Vectorview/Andon Labs) [reported], source: https://www.ycombinator.com/companies/andon-labs (accessed 2026-06-07); LinkedIn public snippets (accessed 2026-06-07); https://www.linkedin.com/posts/emil-froberg_i-co-founded-vectorview-now-andon-labs (accessed 2026-06-07). Specific prior-employer claims (ex-Google, Carnegie Mellon) were not corroborated on a primary source and are omitted.
- published_papers_or_benchmarks: Vending-Bench: Testing long-term coherence in agents (https://andonlabs.com/evals/vending-bench); Vending-Bench 2 (https://andonlabs.com/evals/vending-bench-2); Butter-Bench: Evaluating LLM Controlled Robots for Practical Intelligence (arXiv:2510.21860); Blueprint-Bench; Andon FM (AI-run radio benchmark); Project Vend (real-world AI vending machine, collaboration with Anthropic) [confirmed], source: https://andonlabs.com/ (accessed 2026-06-07); https://arxiv.org/abs/2510.21860 (accessed 2026-06-07); https://www.anthropic.com/research/project-vend-2 (accessed 2026-06-07)
- total_raised: unknown (PitchBook reports ~$500K; Tracxn lists unfunded, sources directly conflict) [unknown], source: https://pitchbook.com/profiles/company/541549-09 (accessed 2026-06-07, ~$500K via search snippet, fetcher 403); https://tracxn.com/d/companies/andonlabs (accessed 2026-06-07, lists unfunded). YC W24 participation confirmed; specific raise amount not corroborated by a primary/announcement source.
- last_round: Y Combinator W24 (pre-seed); raise amount unconfirmed [reported], source: https://www.ycombinator.com/companies/andon-labs (accessed 2026-06-07). YC W24 batch participation confirmed; PitchBook ~$500K is single-source and conflicts with Tracxn's 'unfunded'.
- notable_investors: Y Combinator (W24) [reported], source: https://www.ycombinator.com/companies/andon-labs (accessed 2026-06-07). YC W24 confirmed. Additional names (Breakpoint Capital, Juniper Ventures, Phosphor Capital, Superangel, Seldon Lab) appear only in PitchBook/Tracxn search snippets, not on a primary source, and Tracxn lists the company as unfunded, so they are not independently confirmed and are excluded pending verification.
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown], source: Anecdotal only: Stockholm AI cafe 'Mona' reportedly earned ~44,000 SEK (~$4,659) in first two weeks (https://www.businesstoday.in/, accessed 2026-06-07). Not a company-level revenue figure.
- soc2: unknown [unknown], source: No SOC 2 attestation or trust/security page found as of 2026-06-07
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: No dedicated trust/security page found as of 2026-06-07
- what_they_sell: evals [confirmed], source: https://andonlabs.com/ (accessed 2026-06-07); https://www.anthropic.com/research/project-vend-2 (accessed 2026-06-07). Builds AI agent benchmarks/evaluations (Vending-Bench, Butter-Bench, Blueprint-Bench, Andon FM) plus real-world autonomous deployments. Arguably mixed given deployment/control-research work.
- open_source: unknown [unknown], source: No clear public OSS product/license found as of 2026-06-07; benchmarks published with papers but licensing not confirmed.
- license: unknown [unknown]
- deployment_model: unknown [unknown], source: Vendor sells benchmarks/evals and runs its own deployments; commercial delivery model not publicly documented as of 2026-06-07
- maturity: GA (benchmarks publicly published; autonomous deployments live) [reported], source: https://andonlabs.com/ (accessed 2026-06-07); https://www.anthropic.com/research/project-vend-2 (accessed 2026-06-07); https://fortune.com/2026/06/02/... (accessed 2026-06-07)
- notable_customers: Anthropic (verified, frontier-lab tie); xAI (verified, frontier-lab tie) [reported], source: Anthropic names Andon Labs as a partner on Project Vend on its own site (https://www.anthropic.com/research/project-vend-2, accessed 2026-06-07: 'our partners at Andon Labs'), corroborated by Fortune (https://fortune.com/2026/06/02/..., accessed 2026-06-07). xAI 'Grokbox' built with Andon Labs confirmed by xAI's own Grok account (https://x.com/grok/status/1947365557248135298, accessed 2026-06-07). NOTE: these are confirmed collaborations/partnerships, not confirmed paying customers; 'verified' reflects third-party (Anthropic/xAI) confirmation of the relationship, not a commercial contract.
- sources:
  - https://andonlabs.com/ (accessed 2026-06-07)
  - https://andonlabs.com/evals/vending-bench (accessed 2026-06-07)
  - https://andonlabs.com/evals/vending-bench-2 (accessed 2026-06-07)
  - https://andonlabs.com/evals/butter-bench (accessed 2026-06-07)
  - https://andonlabs.com/join (accessed 2026-06-07)
  - https://arxiv.org/abs/2510.21860 (accessed 2026-06-07)
  - https://www.ycombinator.com/companies/andon-labs (accessed 2026-06-07)
  - https://tracxn.com/d/companies/andonlabs/__kbDcsnD7GXkDkPhJe7NzhyYdc1aYNmLVZaGPytuX8Ck (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/541549-09 (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/andon-labs (accessed 2026-06-07)
  - https://www.linkedin.com/company/andonlabs (accessed 2026-06-07)
  - https://www.linkedin.com/posts/emil-froberg_i-co-founded-vectorview-now-andon-labs-activity-7269617615793238016-BRZ9 (accessed 2026-06-07)
  - https://www.linkedin.com/posts/andonlabs_vectorview-is-now-andon-labs-we-help-frontier-activity-7270578670040170497-GIyX (accessed 2026-06-07)
  - https://fortune.com/2026/06/02/anthropic-office-vending-machine-ai-agents-vendo-andon-lukas-petersson/ (accessed 2026-06-07)
  - https://www.pymnts.com/artificial-intelligence-2/2026/andon-labs-handed-an-ai-a-cafe-and-business-boomed/ (accessed 2026-06-07)
  - https://andonlabs.com/blog/ai-cafe-stockholm (accessed 2026-06-07)
  - https://x.com/andonlabs/status/1943182987371098151 (accessed 2026-06-07)
  - https://x.com/grok/status/1947365557248135298 (accessed 2026-06-07)
  - https://www.businesstoday.in/amp/technology/story/meet-mona-the-ai-running-a-real-cafe-in-stockholm-527972-2026-04-29 (accessed 2026-06-07)
  - https://www.cognitiverevolution.ai/autonomous-organizations-vending-bench-beyond-w-lukas-petersson-axel-backlund-of-andon-labs/ (accessed 2026-06-07)

## Sepal AI, rank #13
- slug: sepal-ai
- segment: Commercial vendors
- website: https://www.sepalai.com/
- focus_areas: Enterprise Workflows, Long-Horizon, Math
- positioning: Sepal AI is a YC-backed (S24) San Francisco data-research company that builds high-quality training data, expert-graded evaluation benchmarks, and reinforcement-learning environments for frontier LLMs, drawing on a network of 20k+ domain experts (PhDs, finance, medical, STEM). It was acquired by Mercor in February 2026.
- best_fit: Buyers needing expert-validated evaluation environments and RL/training data for complex domains (notably finance/spreadsheet analyst workflows and advanced science), note the team is now part of Mercor following the Feb 2026 acquisition.
- overall_confidence: medium
- founded_year: 2024 [confirmed], source: https://www.ycombinator.com/companies/sepal-ai (accessed 2026-06-07); founded 2024, YC S24
- status: acquired [confirmed], source: https://www.orrick.com/en/News/2026/02/Mercor-Acquires-Sepal-AI and https://www.linkedin.com/posts/mercor-ai_today-were-welcoming-sepal-ai-to-mercor-activity-7424897704905826304-N_PJ (accessed 2026-06-07); Mercor acquired Sepal AI, announced 2026-02-06, corroborated by founder and Mercor LinkedIn posts
- hq_location: San Francisco, USA [confirmed], source: https://www.ycombinator.com/companies/sepal-ai and https://www.linkedin.com/company/sepalai (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: ~13-15 core team (YC team size 15; getlatka 13 for 2024). LinkedIn public snippet shows 51-200 band (likely includes contract experts) [reported], source: https://www.ycombinator.com/companies/sepal-ai (team size 15), https://getlatka.com/companies/sepalai.com (13, 2024) and https://www.linkedin.com/company/sepalai (51-200 band) (accessed 2026-06-07)
- headcount_band: unknown [unknown], source: Conflicting signals: YC team size 15 (suggests 11-50) vs LinkedIn 51-200 band (likely inflated by contract experts). Cannot cleanly resolve to a single band, so left unknown. (https://www.ycombinator.com/companies/sepal-ai, https://www.linkedin.com/company/sepalai, accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: https://www.sepalai.com/careers (accessed 2026-06-07); careers page lists roles but exact count not retrievable. Company acquired by Mercor Feb 2026, so roles may have transferred/closed
- has_researchers: yes [reported], source: https://www.ycombinator.com/companies/sepal-ai and https://www.orrick.com/en/News/2026/02/Mercor-Acquires-Sepal-AI (accessed 2026-06-07); hires Applied Research Engineers, runs specialized research projects, engages 20k+ PhDs/domain experts
- researcher_count: unknown [unknown]
- researcher_backgrounds: Co-founders ex-Turing (built/scaled the LLM-trainer business; Robi Lin scaled trainers 50 to 800+; Kat Hu managed 500+ AI trainers); Co-founder Robi Lin formerly at Bain & Co.; co-founder Kat Hu former McKinsey consultant; Co-founder Fedor early engineer at Vercel and Newfront; Engages 20k+ network of academic PhDs and domain professionals (STEM, medical, finance, business) [reported], source: https://www.ycombinator.com/companies/sepal-ai (accessed 2026-06-07)
- published_papers_or_benchmarks: SheetBench-50, first public financial-analyst-grade benchmark of AI agents on real spreadsheet/financial workflows (50 tasks), built in partnership with HUD; tasks validated by finance pros from PwC, Cisco, Charles Schwab, Fannie Mae [confirmed], source: https://www.hud.ai/case-studies/sheetbench-50 and https://huggingface.co/datasets/hud-evals/SheetBench-50 (accessed 2026-06-07)
- total_raised: ~$500K disclosed (single pre-seed round, Sep 2024) per aggregators; YC profile separately states 'several million dollars from leading investors' (unresolved conflict) [reported], source: https://www.crunchbase.com/organization/sepal-ai, https://startupintros.com/orgs/sepal-ai, https://dealigence.vc/company/sepal-ai (all report $500K, 1 round) vs https://www.ycombinator.com/companies/sepal-ai ('several million') (accessed 2026-06-07)
- last_round: Pre-seed, ~$500K, 2024-09-25 (per Crunchbase aggregator; not independently confirmed by a primary announcement) [reported], source: https://www.crunchbase.com/funding_round/sepal-ai-pre-seed--fda22c6a and https://dealigence.vc/company/sepal-ai (accessed 2026-06-07)
- notable_investors: Y Combinator; Metaplanet Holdings; SID Venture Partners; Sterling Road; Team Ignite Ventures [reported], source: https://startupintros.com/orgs/sepal-ai and https://www.crunchbase.com/organization/sepal-ai (via search) (accessed 2026-06-07); consistent across multiple funding aggregators but no primary press release
- valuation: unknown [unknown]
- revenue_signals: Third-party (getlatka) claims ~$2M revenue with a 13-person team in 2024, single unverified source, not vendor-confirmed [reported], source: https://getlatka.com/companies/sepalai.com (accessed 2026-06-07)
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: mixed [confirmed], source: https://www.ycombinator.com/companies/sepal-ai and https://www.orrick.com/en/News/2026/02/Mercor-Acquires-Sepal-AI (accessed 2026-06-07); training data, evaluation benchmarks, and RL environments backed by a 20k+ expert network
- open_source: no [estimated], source: No public OSS repos identified for Sepal itself; product is a data/eval/RL-environment service. SheetBench-50 is hosted on HUD's HuggingFace org (hud-evals), not Sepal's own OSS
- license: unknown [unknown]
- deployment_model: unknown [unknown]
- maturity: GA [estimated], source: https://www.ycombinator.com/companies/sepal-ai (accessed 2026-06-07); claims multiple Fortune 500 and AI-lab paying customers, indicating commercially available services. Note: acquired by Mercor Feb 2026
- notable_customers: Top AI research labs (unnamed; frontier-lab ties referenced in Mercor acquisition rationale) (self-claimed, frontier-lab tie); Multiple Fortune 500 companies (unnamed) (self-claimed); HUD (co-builder/collaboration partner on SheetBench-50, NOT a customer) (verified) [reported], source: https://www.ycombinator.com/companies/sepal-ai (Fortune 500 + AI-lab claims, self-claimed) and https://www.hud.ai/case-studies/sheetbench-50 (HUD collaboration on benchmark, verified as a partner not a customer) (accessed 2026-06-07)
- sources:
  - https://www.sepalai.com/ (accessed 2026-06-07)
  - https://www.sepalai.com/careers (accessed 2026-06-07)
  - https://www.ycombinator.com/companies/sepal-ai (accessed 2026-06-07)
  - https://www.orrick.com/en/News/2026/02/Mercor-Acquires-Sepal-AI (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/sepal-ai (accessed 2026-06-07)
  - https://www.crunchbase.com/funding_round/sepal-ai-pre-seed--fda22c6a (accessed 2026-06-07)
  - https://startupintros.com/orgs/sepal-ai (accessed 2026-06-07)
  - https://www.linkedin.com/company/sepalai (accessed 2026-06-07)
  - https://www.hud.ai/case-studies/sheetbench-50 (accessed 2026-06-07)
  - https://huggingface.co/datasets/hud-evals/SheetBench-50 (accessed 2026-06-07)
  - https://getlatka.com/companies/sepalai.com (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/639950-14 (accessed 2026-06-07)

## HUD, rank #14
- slug: hud
- segment: Commercial vendors
- website: https://www.hud.ai
- focus_areas: Computer Use, Enterprise Workflows
- positioning: HUD (YC W25, formerly hud.so) is a platform for building reinforcement-learning environments and evaluations for computer-use and browser agents. It lets teams wrap real software/code as agent-callable tools in isolated containers, define tasks and rewards, and run evals/RL at scale via an open-source SDK plus a cloud-hosted gateway. It maintains public benchmarks (OSWorld-Verified contributions, SheetBench-50) and positions frontier AI labs and agent-first startups as its target customers.
- best_fit: Teams that need to benchmark or RL-train computer-use/browser agents against real-software tasks with reproducible, containerized environments.
- overall_confidence: medium
- founded_year: 2025 [confirmed], source: https://www.ycombinator.com/companies/hud (accessed 2026-06-07)
- status: active [confirmed], source: https://www.ycombinator.com/companies/hud (accessed 2026-06-07)
- hq_location: San Francisco, USA [confirmed], source: https://www.ycombinator.com/companies/hud (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: no [estimated], source: https://www.ycombinator.com/companies/hud/jobs (accessed 2026-06-07) - listed roles are San Francisco (not remote)
- current_headcount: ~15 (per YC profile, accessed 2026-06-07) [reported], source: https://www.ycombinator.com/companies/hud (accessed 2026-06-07) - team size 15 per YC profile
- headcount_band: 11-50 [reported], source: https://www.ycombinator.com/companies/hud (accessed 2026-06-07) - ~15 reported
- headcount_growth: unknown [unknown]
- open_roles_count: 5 [reported], source: https://www.ycombinator.com/companies/hud/jobs (accessed 2026-06-07) - ~5 SF roles listed; counts fluctuate, treated as reported
- has_researchers: yes [reported], source: https://www.ycombinator.com/companies/hud ; https://www.workatastartup.com/companies/hud (accessed 2026-06-07) - team described as including IOI/IPhO Olympiad medalists and researchers with ICLR/NeurIPS publications; 'Research Engineer' roles open
- researcher_count: unknown [unknown]
- researcher_backgrounds: Jay Ram (CEO) - consumer apps, ML/quant research; Lorenss Martinsons (CPO) - Cognitive Science, Yale; Parth Patel (CTO) - evals and RL environments; Team reported to include International Olympiad medalists (IOI, IPhO) and researchers with ICLR/NeurIPS publications [reported], source: https://www.ycombinator.com/companies/hud ; https://www.workatastartup.com/companies/hud ; https://www.linkedin.com/in/parth220/ (accessed 2026-06-07)
- published_papers_or_benchmarks: OSWorld-Verified (369+ real-world desktop tasks; HUD/'Human Data' acknowledged among institutions providing feedback/fixes, per XLANG Lab); SheetBench-50 (financial-analyst spreadsheet benchmark, developed with Sepal AI; per HUD case study) [reported], source: https://xlang.ai/blog/osworld-verified (acknowledges 'Human Data' / hud.so among feedback institutions; HUD contribution reported not independently confirmed) ; SheetBench-50 self-reported on https://www.hud.ai/case-studies/sheetbench-50 (accessed 2026-06-07)
- total_raised: unknown [unknown], source: A seed round is confirmed (Exceptional Capital portfolio: 'Seed Invested') but amount undisclosed. Secondary figures ($2M, $15M, $21M) in search snippets conflate with an unrelated same-named Israeli company (runtime code sensor, Square Peg Capital). No clean primary amount for hud.ai isolated. Treated as unknown.
- last_round: Seed (amount undisclosed) [reported], source: https://www.exceptionalcap.com/portfolio (accessed 2026-06-07) - HUD listed at 'Seed Stage / Seed Invested'; amount not disclosed
- notable_investors: Y Combinator (W25 batch); Exceptional Capital [reported], source: Y Combinator: https://www.ycombinator.com/companies/hud (W25). Exceptional Capital: https://www.exceptionalcap.com/portfolio lists HUD as a seed-stage portfolio company (accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: https://www.hud.ai/dpa (Data Processing Addendum) [reported], source: https://www.hud.ai/dpa surfaced via search (accessed 2026-06-07); no dedicated trust/security page or SOC 2/ISO certification found
- what_they_sell: environments [confirmed], source: https://github.com/hud-evals/hud-python ; https://docs.hud.ai/ (accessed 2026-06-07)
- open_source: yes [confirmed], source: https://github.com/hud-evals/hud-python (accessed 2026-06-07)
- license: MIT [confirmed], source: https://github.com/hud-evals/hud-python (accessed 2026-06-07) - MIT confirmed via repo license field on re-fetch
- deployment_model: managed-hosted + self-hosted (open-source SDK; cloud platform with local CLI execution and an OpenAI-compatible model gateway at inference.hud.ai) [confirmed], source: https://docs.hud.ai/ ; https://github.com/hud-evals/hud-python (accessed 2026-06-07)
- maturity: GA [estimated], source: https://pypi.org/project/hud-python/ ; https://docs.hud.ai/ (accessed 2026-06-07) - public OSS SDK with regular releases and self-serve docs/login; no formal GA label found
- notable_customers: DoorDash (self-claimed); UiPath (self-claimed); Sharpe (self-claimed); OpenAI (self-claimed, frontier-lab tie); Anthropic (self-claimed, frontier-lab tie) [reported], source: DoorDash/UiPath/Sharpe self-claimed via HUD homepage case studies (https://www.hud.ai/, accessed 2026-06-07). OpenAI/Anthropic: HUD positions frontier labs as customers; the only third-party reference (https://xlang.ai/blog/osworld-verified) co-acknowledges HUD ('Human Data'/hud.so) alongside OpenAI and Anthropic as OSWorld-Verified feedback contributors - this is benchmark collaboration, NOT confirmation of a paid/customer relationship, so kept self-claimed (not verified).
- sources:
  - https://www.ycombinator.com/companies/hud (accessed 2026-06-07)
  - https://www.ycombinator.com/companies/hud/jobs (accessed 2026-06-07)
  - https://github.com/hud-evals/hud-python (accessed 2026-06-07)
  - https://pypi.org/project/hud-python/ (accessed 2026-06-07)
  - https://docs.hud.ai/ (accessed 2026-06-07)
  - https://www.hud.ai/ (accessed 2026-06-07)
  - https://www.hud.ai/case-studies/sheetbench-50 (accessed 2026-06-07)
  - https://www.hud.ai/dpa (accessed 2026-06-07)
  - https://xlang.ai/blog/osworld-verified (accessed 2026-06-07)
  - https://foundertrace.com/companies/hud_yc_w25/ (accessed 2026-06-07)
  - https://www.workatastartup.com/companies/hud (accessed 2026-06-07)
  - https://newsletter.semianalysis.com/p/rl-environments-and-rl-for-science (accessed 2026-06-07)
  - https://www.linkedin.com/company/hud-evals (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/hud (accessed 2026-06-07)
  - https://x.com/hud_evals/status/1919262852088570225 (accessed 2026-06-07)

## Vals AI, rank #15
- slug: vals-ai
- segment: Commercial vendors
- website: https://www.vals.ai
- focus_areas: unknown
- positioning: Vals AI is an independent, third-party benchmarking and evaluation platform that scores LLMs and AI applications (copilots, RAG, agents) on rigorous, domain-specific tasks in regulated fields such as legal, finance, healthcare, tax and coding. It publishes public leaderboards (e.g., the Vals Index, Finance Agent benchmark, Vals Legal AI Report) and sells private evaluation infrastructure to labs and enterprise engineering teams.
- best_fit: Buyers who need neutral, domain-specific (legal/finance/healthcare) benchmarking and ongoing evaluation of LLM applications on their own data and tasks.
- overall_confidence: medium
- founded_year: 2023 [reported], source: Tracxn, Grokipedia, QA-Financial founder coverage (accessed 2026-06-07); note Crunchbase/CB Insights list 2024 and first press coverage is April 2024
- status: active [confirmed], source: https://www.vals.ai/home (accessed 2026-06-07)
- hq_location: San Francisco, USA [reported], source: https://www.linkedin.com/company/vals-ai (public snippet, accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: ~12 people (getLatka, 2025); LinkedIn lists 11-50 employees / ~19 associated profiles [reported], source: https://getlatka.com/companies/vals.ai/funding (accessed 2026-06-07); https://www.linkedin.com/company/vals-ai (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/vals-ai (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown]
- has_researchers: yes [reported], source: arXiv:2508.00828 authored by Vals AI team; founders ex-Stanford AI master's; Stanford collaborations (accessed 2026-06-07)
- researcher_count: unknown [unknown]
- researcher_backgrounds: Co-founder/CEO Rayan Krishnan - ex-Stanford AI master's; Co-founder/CTO Langston Nashold - ex-Stanford AI master's; Founding engineer Rez (Reza) Havaei; Collaborations with Stanford researchers and domain experts in law, finance, accounting [reported], source: https://qa-financial.com/industry-on-a-mission-the-long-road-to-uniform-ai-testing/ (accessed 2026-06-07); https://www.techtimes.com/articles/303524 (accessed 2026-06-07)
- published_papers_or_benchmarks: Finance Agent Benchmark: Benchmarking LLMs on Real-world Financial Research Tasks - arXiv:2508.00828; Vals Legal AI Report (VLAIR), Feb 2025 - https://www.vals.ai; Vals Index / domain leaderboards (TaxEval, CorpFin, MedCode, LegalBench, CaseLaw, ContractLaw, Finance Agent) - https://www.vals.ai; Finance Agent benchmark dataset on Hugging Face - https://huggingface.co/datasets/vals-ai/finance_agent_benchmark [confirmed], source: https://arxiv.org/abs/2508.00828 (accessed 2026-06-07); https://www.vals.ai/home (accessed 2026-06-07); https://huggingface.co/datasets/vals-ai/finance_agent_benchmark (accessed 2026-06-07)
- total_raised: unknown [unknown], source: getLatka states Vals AI is bootstrapped with $0 raised (https://getlatka.com/companies/vals.ai/funding, accessed 2026-06-07). A widely-cited '$5M seed / Sequoia, Bloomberg Beta, Pear VC, 8VC, J12' appears to be aggregator data conflated with an unrelated company (Vallor, a Miami procurement-AI startup that raised a $4M Bloomberg Beta-led seed in April 2025) and could not be confirmed.
- last_round: unknown [unknown], source: No primary announcement of a Vals AI funding round found; getLatka reports bootstrapped/$0 raised (accessed 2026-06-07). The '$5M seed, July 29, 2024' figure on aggregators is unconfirmed and likely conflated with another company.
- notable_investors: unknown [unknown], source: The investor list (Sequoia Capital, Bloomberg Beta, Pear VC, 8VC, J12) circulating on aggregators could not be verified and appears conflated with an unrelated company (Vallor). No primary funding announcement found; getLatka reports the company as bootstrapped.
- valuation: unknown [unknown], source: getLatka lists a $4M valuation as an estimate (https://getlatka.com/companies/vals.ai, accessed 2026-06-07); not corroborated by any primary or credible third-party source.
- revenue_signals: ~$1.3M revenue/ARR in 2025 (getLatka self-reported/estimated figure; not vendor-confirmed) [reported], source: https://getlatka.com/companies/vals.ai/funding (accessed 2026-06-07)
- soc2: claimed-unverified (SOC 2 badge displayed on product page; type not specified; no trust/audit-registry confirmation) [reported], source: https://www.vals.ai/product (accessed 2026-06-07)
- other_certifications: GDPR (compliance badge displayed on product page; unverified) [reported], source: https://www.vals.ai/product (accessed 2026-06-07)
- security_page: unknown (no dedicated /security or /trust page found; only SOC 2 and GDPR badges on product page) [unknown], source: https://www.vals.ai/product (accessed 2026-06-07)
- what_they_sell: evals [confirmed], source: https://www.vals.ai/product (accessed 2026-06-07); https://www.vals.ai/home (accessed 2026-06-07)
- open_source: yes (benchmark code/datasets published, e.g., Finance Agent benchmark; platform itself is proprietary SaaS) [confirmed], source: https://github.com/vals-ai/finance-agent (accessed 2026-06-07)
- license: MIT (finance-agent benchmark repo) [confirmed], source: https://github.com/vals-ai/finance-agent (accessed 2026-06-07)
- deployment_model: managed-hosted (SaaS) with API/SDK/CLI; web app at platform.vals.ai [confirmed], source: https://www.vals.ai/product (accessed 2026-06-07)
- maturity: GA (public benchmarks/leaderboards live; private evaluation infrastructure offered, partly early access) [reported], source: https://www.vals.ai/product (accessed 2026-06-07); https://www.vals.ai/about (accessed 2026-06-07)
- notable_customers: Reed Smith (law firm; VLAIR benchmarking consortium partner, not a paying customer) (self-claimed); Fisher Phillips (law firm; VLAIR benchmarking consortium partner, not a paying customer) (self-claimed); McDermott Will & Emery (law firm; VLAIR benchmarking consortium partner, not a paying customer) (self-claimed); Ogletree Deakins (law firm; VLAIR benchmarking consortium partner, not a paying customer) (self-claimed); Harvey (legal AI vendor evaluated in VLAIR; not a stated customer) (self-claimed); CoCounsel/Thomson Reuters (legal AI vendor evaluated in VLAIR; not a stated customer) (self-claimed); Alexi (legal AI vendor evaluated in VLAIR; not a stated customer) (self-claimed) [reported], source: https://www.lawnext.com/2025/05/vals-ai-issues-open-call-for-vendors-to-participate-in-its-legal-research-and-other-legal-ai-benchmarking-studies.html (accessed 2026-06-07); https://finance.yahoo.com/news/vals-legal-ai-report-establishes-160000601.html (accessed 2026-06-07). These are benchmarking-study consortium partners / evaluated vendors, NOT confirmed paying platform customers; no verified customer relationships found.
- sources:
  - https://www.vals.ai/home (accessed 2026-06-07)
  - https://www.vals.ai/about (accessed 2026-06-07)
  - https://www.vals.ai/product (accessed 2026-06-07)
  - https://www.linkedin.com/company/vals-ai (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/vals-ai (accessed 2026-06-07)
  - https://tracxn.com/d/companies/vals-ai/__Aeq7C2n56rLfgsWjTrbrPIwiOteKWlKhIWYPbapLuow (accessed 2026-06-07)
  - https://getlatka.com/companies/vals.ai/funding (accessed 2026-06-07)
  - https://qa-financial.com/industry-on-a-mission-the-long-road-to-uniform-ai-testing/ (accessed 2026-06-07)
  - https://www.techtimes.com/articles/303524/20240412/standardized-ai-performance-test-tested-out-new-startup.htm (accessed 2026-06-07)
  - https://www.bloomberg.com/news/newsletters/2024-04-11/this-startup-is-trying-to-test-how-well-ai-models-actually-work (accessed 2026-06-07)
  - https://www.deeplearning.ai/the-batch/vals-ai-evaluates-large-language-models-on-industry-specific-tasks/ (accessed 2026-06-07)
  - https://www.lawnext.com/2025/05/vals-ai-issues-open-call-for-vendors-to-participate-in-its-legal-research-and-other-legal-ai-benchmarking-studies.html (accessed 2026-06-07)
  - https://finance.yahoo.com/news/vals-legal-ai-report-establishes-160000601.html (accessed 2026-06-07)
  - https://arxiv.org/abs/2508.00828 (accessed 2026-06-07)
  - https://huggingface.co/datasets/vals-ai/finance_agent_benchmark (accessed 2026-06-07)
  - https://github.com/vals-ai/finance-agent (accessed 2026-06-07)
  - https://www.legaltechnologyhub.com/vendors/vals-ai/ (accessed 2026-06-07)

## Halluminate, rank #16
- slug: halluminate
- segment: Commercial vendors
- website: https://www.halluminate.ai/
- focus_areas: Computer Use, Enterprise Workflows
- positioning: Halluminate (YC S25, founded 2024, San Francisco) builds managed reinforcement-learning sandbox environments, simulated applications, and human/annotation data plus evaluation benchmarks (WebBench, BrowserBench, Westworld) to train and test computer-use and browser AI agents. Its 2026 site positioning has narrowed toward 'RL environments for financial services' (investment banking, private equity, consulting).
- best_fit: Foundation-model labs and browser/computer-use agent teams needing deterministic, managed RL sandboxes plus expert eval/annotation data, increasingly for finance workflows.
- overall_confidence: medium
- founded_year: 2024 [reported], source: https://www.ycombinator.com/companies/halluminate (accessed 2026-06-07)
- status: active [confirmed], source: https://www.halluminate.ai/ (accessed 2026-06-07)
- hq_location: San Francisco, CA, USA [confirmed], source: https://www.ycombinator.com/companies/halluminate ; https://www.linkedin.com/company/halluminate (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: ~5-17 (YC profile lists team size 5; LinkedIn lists company size 2-10 with ~17 associated members, accessed 2026-06-07). getlatka's '12 as of 2025-09-14' is a third-party estimate and conflicts with YC/LinkedIn. [estimated], source: https://www.ycombinator.com/companies/halluminate ; https://www.linkedin.com/company/halluminate (accessed 2026-06-07)
- headcount_band: 1-10 [estimated], source: https://www.ycombinator.com/companies/halluminate (team size 5) ; https://www.linkedin.com/company/halluminate (2-10 employees) (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown]
- has_researchers: yes [reported], source: https://www.paraform.com/company/halluminate/cmo0vioko000e0djsvyvu9n6m (accessed 2026-06-07), hiring 'Founding Member of Technical Staff (Research/Post-Training)'; CEO led research at Capital One Labs per YC profile
- researcher_count: unknown [unknown]
- researcher_backgrounds: Jerry Wu (co-founder/CEO): ex-Capital One Labs (led product and research; launched an early AI agent in banking); Cornell CS & Economics; Wyatt Marshall (co-founder): Cornell Milstein Scholar; large-scale data engineering at two early-stage NYC startups [reported], source: https://www.ycombinator.com/companies/halluminate (accessed 2026-06-07)
- published_papers_or_benchmarks: WebBench, browser agent benchmark (~5,750 READ/ACTION tasks across 500+ websites): https://github.com/Halluminate/WebBench ; https://www.halluminate.ai/blog/benchmark; BrowserBench, benchmark for browser infrastructure stealth (292 tasks/292 sites): https://github.com/Halluminate/browserbench ; https://www.halluminate.ai/blog/browserbench; Westworld, simulated-internet web agent benchmark/RL environment: https://github.com/Halluminate/westworld ; https://www.halluminate.ai/blog/westworld [confirmed], source: https://github.com/Halluminate (accessed 2026-06-07)
- total_raised: undisclosed/conflicting (YC S25-backed; PitchBook reports ~$160K; some aggregators report ~$500K; getlatka claims $0/bootstrapped, figures conflict and none confirmed by an official announcement) [reported], source: https://pitchbook.com/profiles/company/616571-92 ; https://www.ycombinator.com/companies/halluminate (accessed 2026-06-07)
- last_round: Y Combinator S25 (Summer 2025); seed/pre-seed amount and date not officially disclosed [reported], source: https://www.ycombinator.com/companies/halluminate (accessed 2026-06-07)
- notable_investors: Y Combinator (S25); Orange Collective; Antigravity Capital; Batch Ventures; Team Ignite Ventures; Transpose Platform Management [reported], source: https://pitchbook.com/profiles/company/616571-92 (via search summary) ; https://www.ycombinator.com/companies/halluminate ; https://www.orangecollective.vc/portfolio/halluminate ; https://antigravity.capital/portfolio/halluminate (accessed 2026-06-07)
- valuation: unknown (getlatka lists a $4M estimate, but it is an unverified third-party estimate from a source with internally inconsistent data for this company) [unknown]
- revenue_signals: unknown (getlatka estimates ~$1.3M ARR for 2025, but this is an unverified third-party estimate from a source with internally inconsistent data, e.g. it also claims $0 raised/bootstrapped despite YC and angel backing) [estimated], source: https://getlatka.com/companies/halluminate.ai (accessed 2026-06-07)
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: mixed [confirmed], source: https://www.halluminate.ai/ ; https://www.ycombinator.com/companies/halluminate ; https://news.ycombinator.com/item?id=44865290 (accessed 2026-06-07), RL/sandbox environments for computer-use agents plus human/annotation data and evaluation benchmarks
- open_source: yes [confirmed], source: https://github.com/Halluminate (accessed 2026-06-07)
- license: Mixed: WebBench (MIT), westworld (Apache-2.0), noodle-flights (MIT), browserbench (no license shown) [confirmed], source: https://github.com/Halluminate (accessed 2026-06-07)
- deployment_model: managed-hosted (fully managed, parallelizable sandbox environments); also bespoke/custom environments for enterprise clients [confirmed], source: https://www.ycombinator.com/companies/halluminate ; https://news.ycombinator.com/item?id=44865290 (accessed 2026-06-07)
- maturity: GA [estimated], source: https://www.ycombinator.com/companies/halluminate (accessed 2026-06-07), states paying customers, indicating commercial availability
- notable_customers: Leading computer-use model labs (unnamed) (self-claimed, frontier-lab tie); The two largest browser agent companies (unnamed) (self-claimed); Frontier labs e.g. OpenAI, Anthropic (per company copy, unnamed/unconfirmed) (self-claimed, frontier-lab tie) [reported], source: https://www.ycombinator.com/companies/halluminate ; https://www.halluminate.ai/blog/westworld (accessed 2026-06-07), vendor's own claims only; no named, third-party-verified customers found
- sources:
  - https://www.halluminate.ai/ (accessed 2026-06-07)
  - https://www.ycombinator.com/companies/halluminate (accessed 2026-06-07)
  - https://news.ycombinator.com/item?id=44865290 (accessed 2026-06-07)
  - https://github.com/Halluminate (accessed 2026-06-07)
  - https://getlatka.com/companies/halluminate.ai (accessed 2026-06-07)
  - https://www.orangecollective.vc/portfolio/halluminate (accessed 2026-06-07)
  - https://antigravity.capital/portfolio/halluminate (accessed 2026-06-07)
  - https://www.halluminate.ai/blog/browserbench (accessed 2026-06-07)
  - https://www.halluminate.ai/blog/benchmark (accessed 2026-06-07)
  - https://www.halluminate.ai/blog/westworld (accessed 2026-06-07)
  - https://www.paraform.com/company/halluminate/cmo0vioko000e0djsvyvu9n6m (accessed 2026-06-07)
  - https://www.linkedin.com/in/jerry-wu-7814b0100/ (accessed 2026-06-07)

## Matrices, rank #17
- slug: matrices
- segment: Commercial vendors
- website: https://matrices.ai
- focus_areas: Computer Use
- positioning: Matrices builds reinforcement-learning training environments for frontier AI labs to train agents that use computers and browsers like humans, described as a 'gamified replica of the internet' where thousands of agents learn via RL. The company frames its mission as 'towards self-driving computers' and says it helps labs train computer-use agents (Operator-class systems). Note: this is the correct browser-native entity (matrices.ai / LinkedIn 'matricesapp'), distinct from the similarly named 'Matrice.ai' computer-vision company and 'Matrix AI Network' blockchain project.
- best_fit: A frontier lab needing large-scale, realistic browser/computer-use RL environments to train and evaluate web-navigating agents.
- overall_confidence: medium
- founded_year: 2023 [reported], source: https://www.linkedin.com/company/matricesapp ; https://tracxn.com/d/companies/matrices/ (accessed 2026-06-07)
- status: active [reported], source: https://www.linkedin.com/company/matricesapp (accessed 2026-06-07); https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents (accessed 2026-06-07)
- hq_location: San Francisco, California, USA [reported], source: https://www.linkedin.com/company/matricesapp (accessed 2026-06-07); https://tracxn.com/d/companies/matrices/ (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: ~19-21 employees (LinkedIn band 11-50; Tracxn '21 employees as of Apr 30, 2026') [reported], source: https://www.linkedin.com/company/matricesapp ; https://tracxn.com/d/companies/matrices/ (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/matricesapp (size band 11-50); https://tracxn.com/d/companies/matrices/ (accessed 2026-06-07)
- headcount_growth: unknown [unknown], source: Note: theinflectionpoint.ai article described team as 'still just 3 people' at an earlier date; current LinkedIn/Tracxn show ~19-21, implying growth, but no quantified period available
- open_roles_count: unknown [unknown], source: https://matrices.ai/careers (accessed 2026-06-07), actively hiring noted but exact count not retrievable (JS-rendered page)
- has_researchers: unknown [unknown]
- researcher_count: unknown [unknown]
- researcher_backgrounds: Co-founder Leonardo Axel Setyanto (Co-Founder/CTO): UT Austin; prior startup engineering (Loku), no frontier-lab pedigree found; Co-founder John Qian: University of Illinois Urbana-Champaign [reported], source: https://www.linkedin.com/in/axelsetyanto/ ; https://www.linkedin.com/in/qianjohn/ (accessed 2026-06-07)
- published_papers_or_benchmarks: unknown [unknown]
- total_raised: $5M (single-source; exact figure reported only by one third-party blog and a careers-page snippet) [reported], source: https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents ; matrices.ai/careers snippet (accessed 2026-06-07). Crunchbase (matrices-f9d0) confirms a Seed round but obfuscates the amount.
- last_round: Seed (amount reported as $5M; date unconfirmed) [reported], source: https://www.crunchbase.com/organization/matrices-f9d0 (confirms Seed stage); https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents (accessed 2026-06-07)
- notable_investors: Index Ventures; AI Grant (Nat Friedman & Daniel Gross); Naval Ravikant [reported], source: https://www.crunchbase.com/organization/matrices-f9d0 (independently lists Index Ventures); https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents (Index, AI Grant, Naval) (accessed 2026-06-07). AI Grant and Naval Ravikant are single-source (blog only).
- valuation: unknown [unknown]
- revenue_signals: Self-claimed '7-figure contracts with multiple/top AI labs'; no verified figure [reported], source: https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents ; matrices.ai/careers snippet (accessed 2026-06-07), vendor self-claim, labs unnamed
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: environments [confirmed], source: https://matrices.ai/ (title: 'Matrices - Training Environments for LLM Agents'); https://www.linkedin.com/company/matricesapp (tagline 'Towards self-driving computers'); https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents (accessed 2026-06-07)
- open_source: no [estimated], source: No public GitHub org or OSS product found as of 2026-06-07
- license: unknown [unknown]
- deployment_model: managed-hosted [estimated], source: https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents (accessed 2026-06-07), inferred from hosted 'replica of the internet' running thousands of agents; not explicitly stated
- maturity: unknown [unknown]
- notable_customers: Unnamed frontier AI labs (described as signing 7-figure contracts; agents like OpenAI 'Operator' referenced as the type they help train) (self-claimed) [reported], source: https://matrices.ai/careers (snippet) ; https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents (accessed 2026-06-07), labs not named; no specific frontier lab confirmed as a customer
- sources:
  - https://matrices.ai/ (accessed 2026-06-07)
  - https://matrices.ai/careers (accessed 2026-06-07)
  - https://www.linkedin.com/company/matricesapp (accessed 2026-06-07)
  - https://theinflectionpoint.ai/p/building-a-fake-internet-for-ai-agents (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/matrices-f9d0 (accessed 2026-06-07)
  - https://www.linkedin.com/in/axelsetyanto/ (accessed 2026-06-07)
  - https://www.linkedin.com/in/qianjohn/ (accessed 2026-06-07)
  - https://tracxn.com/d/companies/matrices/ (accessed 2026-06-07)
  - https://rocketreach.co/matrices-management_b6cf945ec78254fc (accessed 2026-06-07)
  - https://techcrunch.com/2025/09/21/silicon-valley-bets-big-on-environments-to-train-ai-agents/ (accessed 2026-06-07)

## BenchFlow, rank #18
- slug: benchflow
- segment: Commercial vendors
- website: https://www.benchflow.ai/
- focus_areas: Coding, Computer Use, Enterprise Workflows
- positioning: BenchFlow is an early-stage, YC-backed open-source 'environment lab' building evaluation infrastructure and a community Benchmark Hub for AI agents, with products including SkillsBench, ClawsBench (mock workplace environments) and a sandboxed agent runtime. It positions environments as 'the new data' for training and evaluating agents across domains like enterprise workflows, coding, computer use and browser tasks.
- best_fit: Teams needing open-source, reproducible agent evaluation environments and a runtime to benchmark coding/computer-use/workplace agents at low setup cost.
- overall_confidence: medium
- founded_year: 2024 [reported], source: https://startupintros.com/orgs/benchflow (accessed 2026-06-07); https://www.linkedin.com/company/benchflow-ai (accessed 2026-06-07)
- status: active [confirmed], source: https://www.benchflow.ai/ (accessed 2026-06-07); https://github.com/benchflow-ai/benchflow (accessed 2026-06-07), release 0.5.2 dated 2026-06-05
- hq_location: New Castle, DE, USA (incorporation); Bay Area / San Francisco operating presence [reported], source: https://startupintros.com/orgs/benchflow (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: 1-10 employees (LinkedIn shows 2-10 band; ~3 identified on LinkedIn as of 2026-06-07) [reported], source: https://www.linkedin.com/company/benchflow-ai (accessed 2026-06-07); https://startupintros.com/orgs/benchflow (accessed 2026-06-07)
- headcount_band: 1-10 [reported], source: https://www.linkedin.com/company/benchflow-ai (accessed 2026-06-07); https://startupintros.com/orgs/benchflow (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown]
- has_researchers: yes [reported], source: https://www.benchflow.ai/ (accessed 2026-06-07); SkillsBench has an arXiv paper (arXiv:2602.12670) authored under BenchFlow, eval/research-oriented work
- researcher_count: unknown [unknown]
- researcher_backgrounds: Xiangyi Li (founder/CEO), creator of SkillsBench; prior engineering roles per founder interview; Moritz Wallawitsch, early co-founder, reported departure ~Feb 2025 [reported], source: https://www.inverse.com/tech/building-ais-testing-ground-benchflows-mission-as-explained-by-xiangyi-li (accessed 2026-06-07); https://startupintros.com/orgs/benchflow (accessed 2026-06-07); https://www.linkedin.com/in/l1xiangyi/ (accessed 2026-06-07)
- published_papers_or_benchmarks: SkillsBench, 'Benchmarking How Well Agent Skills Work Across Diverse Tasks' (arXiv:2602.12670); 86 tasks across 11 domains with curated Skills and deterministic verifiers; ClawsBench (mock workplace environments: Gmail, Calendar, Drive, Docs, Slack); Benchmark Hub (community ports incl. OS-World, WebArena) [confirmed], source: https://www.benchflow.ai/ (accessed 2026-06-07); https://github.com/benchflow-ai/skillsbench (accessed 2026-06-07); https://arxiv.org/abs/2602.12670 (accessed 2026-06-07)
- total_raised: $1.0M [reported], source: https://startupintros.com/orgs/benchflow (accessed 2026-06-07), single aggregator; no primary press release or official funding announcement located; Crunchbase/PitchBook not directly accessible
- last_round: Seed, $1M, January 2025 [reported], source: https://startupintros.com/orgs/benchflow (accessed 2026-06-07), single aggregator; not independently confirmed by primary announcement
- notable_investors: Y Combinator; Pear VC; Construct Capital; FAST by GETTYLAB; Ankit Jain (angel) [reported], source: https://startupintros.com/orgs/benchflow (accessed 2026-06-07), single aggregator; not confirmed against an investor's own portfolio page or primary announcement
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown], source: No SOC2 mention or trust page found on official site (accessed 2026-06-07)
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: No dedicated trust/security page found (https://www.benchflow.ai/ accessed 2026-06-07)
- what_they_sell: environments [confirmed], source: https://www.benchflow.ai/ (accessed 2026-06-07), 'A frontier environment lab for AI agents'; environments + evaluation infrastructure (SkillsBench, ClawsBench, runtime)
- open_source: yes [confirmed], source: https://github.com/benchflow-ai/benchflow (accessed 2026-06-07)
- license: Apache-2.0 [confirmed], source: https://github.com/benchflow-ai/benchflow (accessed 2026-06-07)
- deployment_model: API + self-hosted (open-source runtime; sandboxes via Docker/Daytona/Modal); Benchmark Hub managed-hosted [reported], source: https://github.com/benchflow-ai/benchflow (accessed 2026-06-07); https://docs.benchflow.ai/introduction (accessed 2026-06-07); https://news.ycombinator.com/item?id=43440893
- maturity: research preview / early-stage (open-source runtime and Benchmark Hub live and actively released; RFT framework still in development; pre-Series-A YC startup) [estimated], source: https://github.com/benchflow-ai/benchflow (accessed 2026-06-07), release 0.5.2 on 2026-06-05; https://docs.benchflow.ai/introduction (accessed 2026-06-07)
- notable_customers: unknown [unknown], source: No named customers on the official site or any credible third party. Search-summary claim that BenchFlow 'testing infrastructure was featured during the launch of Google's Gemini model' appears only in AI-generated summaries with no primary source and is NOT verified; official site references Gemini only as a supported model, not a partner/customer.
- sources:
  - https://www.benchflow.ai/ (accessed 2026-06-07)
  - https://docs.benchflow.ai/introduction (accessed 2026-06-07)
  - https://github.com/benchflow-ai/benchflow (accessed 2026-06-07)
  - https://github.com/benchflow-ai/skillsbench (accessed 2026-06-07)
  - https://startupintros.com/orgs/benchflow (accessed 2026-06-07)
  - https://www.linkedin.com/company/benchflow-ai (accessed 2026-06-07)
  - https://www.linkedin.com/in/l1xiangyi/ (accessed 2026-06-07)
  - https://www.inverse.com/tech/building-ais-testing-ground-benchflows-mission-as-explained-by-xiangyi-li (accessed 2026-06-07)
  - https://news.ycombinator.com/item?id=43440893 (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/benchflow (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/711737-02 (accessed 2026-06-07)

## Collinear, rank #19
- slug: collinear
- segment: Commercial vendors
- website: https://www.collinear.ai/
- focus_areas: Coding, Computer Use, Enterprise Workflows, Long-Horizon
- positioning: Collinear AI operates a 'Simulation Lab' (SimLab) that builds sandboxed, stateful RL environments simulating enterprise users, tools (Jira, ServiceNow, Shopify, EMR, airline/hotel systems) and multi-step workflows, producing training-ready trajectories, reward signals and evals for agentic models. It also offers synthetic post-training data and LLM-judge evaluation, positioning itself around 'environment-as-a-service' for enterprise long-horizon agents.
- best_fit: Buyers training or evaluating enterprise agents that need realistic, stateful long-horizon simulated workflows (IT support, customer service, finance, HR) with verifiable rewards.
- overall_confidence: medium
- founded_year: 2023 [reported], source: https://www.technologyreview.com/innovator/nazneen-rajani/ and https://www.innovatorsunder35.com/the-list/nazneen-rajani/ (founded after leaving Hugging Face); https://www.crunchbase.com/person/nazneen-rajani-9727 (CEO since Jan 2023); Tracxn (2023). LinkedIn/prospeo list 2024, conflict; 2023 better supported (accessed 2026-06-07)
- status: active [confirmed], source: https://www.collinear.ai/ (accessed 2026-06-07)
- hq_location: Mountain View / Sunnyvale, California, USA [reported], source: https://www.linkedin.com/company/collinearai (HQ Mountain View); prospeo lists Mountain View CA; some databases list San Francisco (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown], source: https://www.collinear.ai/careers states no remote/distributed policy; physical CA office implied (accessed 2026-06-07)
- current_headcount: ~16-23 (About page lists 16 team members; Tracxn ~23 as of 2026-04-30; Crunchbase 1-10; LinkedIn band 11-50; prospeo 11-20) [reported], source: https://www.collinear.ai/about-us (16 named); https://tracxn.com/d/companies/collinearai (~23, 2026-04-30); https://www.crunchbase.com/organization/collinear-ai (1-10); https://www.linkedin.com/company/collinearai (11-50) (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/collinearai (11-50); corroborated by About page (16 members) and Tracxn (~23); note Crunchbase lists 1-10 (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: 10 [confirmed], source: https://www.collinear.ai/careers - 10 roles (Head of People and Talent, Technical Product Lead, ML SWE, Senior Backend SWE, Research Scientist/Engineer, Research Internship, Marketing Lead, Head of Research, Engineering Leader, Account Executive) (accessed 2026-06-07)
- has_researchers: yes [confirmed], source: https://www.collinear.ai/careers (Research Scientist/Engineer, Head of Research roles); https://www.collinear.ai/about-us (team from Hugging Face, Salesforce, Google, Amazon, Stanford) (accessed 2026-06-07)
- researcher_count: unknown [unknown], source: About page lists 16 team members but does not split research vs engineering (accessed 2026-06-07)
- researcher_backgrounds: Founder/CEO Nazneen Rajani: ex-Robustness Research Lead at Hugging Face, ex-Research Scientist at Salesforce, PhD University of Texas at Austin (MIT TR Innovators Under 35); Team described as researchers/engineers from Hugging Face, Salesforce, Google, Amazon, Stanford (per company About page) [reported], source: https://www.collinear.ai/about-us ; https://www.technologyreview.com/innovator/nazneen-rajani/ ; https://www.linkedin.com/in/nazneenrajani (accessed 2026-06-07)
- published_papers_or_benchmarks: unknown [unknown], source: Company blog publishes thought-leadership posts; no formal paper or named public benchmark confirmed (accessed 2026-06-07)
- total_raised: unknown [unknown], source: No disclosed funding amount in any source. Investors named on About page but Tracxn/Crunchbase/prospeo list company as 'unfunded' / no disclosed round (accessed 2026-06-07)
- last_round: unknown [unknown], source: No round stage/amount/date found in public sources (accessed 2026-06-07)
- notable_investors: Engineering Capital; Firestreak Ventures; 112 Capital (11.2 Capital) [reported], source: https://www.collinear.ai/about-us (names Engineering Capital, Firestreak, 112 Capital). PitchBook search snippet additionally lists Khasm Labs and ISV Startup Springboard, single weak source, not included (accessed 2026-06-07)
- valuation: unknown [unknown], source: prospeo lists ~$5.3M but explicitly labels it an industry-average estimate, not a reported figure (accessed 2026-06-07)
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown], source: No trust/security page found; /security returned 404 (accessed 2026-06-07)
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: https://www.collinear.ai/security returned 404 (accessed 2026-06-07)
- what_they_sell: environments [confirmed], source: https://www.collinear.ai/ ; https://blog.collinear.ai/p/rl-env-as-a-service (accessed 2026-06-07)
- open_source: no [estimated], source: No public OSS repos surfaced; product is a hosted simulation platform (accessed 2026-06-07)
- license: unknown [unknown]
- deployment_model: managed-hosted / API (environment endpoints) [reported], source: https://blog.collinear.ai/p/rl-env-as-a-service - 'point your trainer and sampler at Collinear's environment endpoints' (accessed 2026-06-07)
- maturity: unknown [unknown], source: Product pages and blog do not state beta/GA status (accessed 2026-06-07)
- notable_customers: Amazon (self-claimed); ServiceNow (self-claimed); Kore.ai (self-claimed); Matillion (self-claimed); MasterClass (self-claimed); Zoho (self-claimed); HUMAIN (self-claimed); Commonwealth Bank (self-claimed); LaHaus (self-claimed); ParseAI (self-claimed) [reported], source: https://www.collinear.ai/ (customer logos); https://www.collinear.ai/case-studies (Kore.ai and ServiceNow case studies), all published by the vendor, hence self-claimed (accessed 2026-06-07)
- sources:
  - https://www.collinear.ai/ (accessed 2026-06-07)
  - https://www.collinear.ai/about-us (accessed 2026-06-07)
  - https://www.collinear.ai/careers (accessed 2026-06-07)
  - https://blog.collinear.ai/p/rl-env-as-a-service (accessed 2026-06-07)
  - https://www.linkedin.com/company/collinearai (accessed 2026-06-07)
  - https://tracxn.com/d/companies/collinearai/__afhJh0xW8gZpWYbw5rCoeqG-KD4fTP3wJr3zxaPZ6Y0 (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/550057-87 (accessed 2026-06-07)
  - https://www.linkedin.com/in/nazneenrajani (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/collinear-ai (accessed 2026-06-07)

## Refresh, rank #20
- slug: refresh
- segment: Commercial vendors
- website: https://www.refresh.dev
- focus_areas: Coding, Computer Use, Private Codebases
- positioning: Refresh (YC X25) builds simulation engines / RL environments with verifiable rewards for coding and computer use, partnering with frontier labs and enterprises to train AI software-engineering and computer-use 'coworker' capabilities across terminal and GUI.
- best_fit: Frontier labs needing custom RL training environments and datasets for software-engineering and computer-use agent capabilities.
- overall_confidence: medium
- founded_year: 2025 [confirmed], source: https://www.ycombinator.com/companies/refresh accessed 2026-06-07 (YC Spring 2025 / X25, founded 2025); https://www.linkedin.com/company/refresh-dot-dev accessed 2026-06-07
- status: active [confirmed], source: https://www.refresh.dev/ accessed 2026-06-07; https://www.ycombinator.com/companies/refresh accessed 2026-06-07
- hq_location: San Francisco, CA, USA [confirmed], source: https://www.ycombinator.com/companies/refresh accessed 2026-06-07; https://www.linkedin.com/company/refresh-dot-dev accessed 2026-06-07
- other_locations: unknown [unknown]
- distributed_remote: no [estimated], source: https://www.refresh.dev/careers accessed 2026-06-07 (roles listed San Francisco, in-person)
- current_headcount: ~8 employees (as of 2026-06-07) [reported], source: https://www.ycombinator.com/companies/refresh accessed 2026-06-07 (lists 8 employees); https://www.linkedin.com/company/refresh-dot-dev accessed 2026-06-07 (public snippet ~7)
- headcount_band: 1-10 [confirmed], source: https://www.ycombinator.com/companies/refresh accessed 2026-06-07 (8 employees); https://www.linkedin.com/company/refresh-dot-dev accessed 2026-06-07
- headcount_growth: unknown [unknown]
- open_roles_count: 3 [reported], source: https://www.refresh.dev/careers accessed 2026-06-07 (3 SF full-time roles listed)
- has_researchers: yes [reported], source: https://www.ycombinator.com/launches/Ncy-refresh-turning-real-work-into-rl-training-grounds accessed 2026-06-07 (mechanistic interpretability work); https://www.refresh.dev/careers accessed 2026-06-07 (Research Engineer, Benchmarking role)
- researcher_count: unknown [unknown]
- researcher_backgrounds: Christopher Settles (CEO), ex-Uber AI ML tech lead; CS degree from UIUC; Erik Quintanilla (CTO), ex-Capital One, ex-Amazon (computer vision / data scraping); Team described as ex-Uber ML and ex-Amazon scraping; reportedly turned down Scale AI offers [reported], source: https://www.ycombinator.com/companies/refresh accessed 2026-06-07; https://www.ycombinator.com/launches/Ncy-refresh-turning-real-work-into-rl-training-grounds accessed 2026-06-07
- published_papers_or_benchmarks: unknown [unknown], source: SWE-Bench, Terminal-Bench, OS-World on YC launch page are external benchmarks they target, not their own publications. https://www.ycombinator.com/launches/Ncy-refresh-turning-real-work-into-rl-training-grounds accessed 2026-06-07
- total_raised: unknown [unknown], source: YC-backed (X25). No total disclosed in any primary source; an unverified ~$500K pre-seed figure surfaced in a LinkedIn snippet only, not confirmed.
- last_round: unknown [unknown], source: YC investment implied by batch participation; specific round stage/amount/date not in any primary source as of 2026-06-07.
- notable_investors: Y Combinator [reported], source: https://www.ycombinator.com/companies/refresh accessed 2026-06-07 (YC X25 batch participation). Reported angel/Weekend Fund participation could not be confirmed against any primary source.
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown], source: No security/trust page found; https://www.refresh.dev/security returns 404 (accessed 2026-06-07)
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: https://www.refresh.dev/security returns 404 (accessed 2026-06-07)
- what_they_sell: environments [confirmed], source: https://www.refresh.dev/ accessed 2026-06-07 (simulation engines for coding and computer use); https://www.ycombinator.com/companies/refresh accessed 2026-06-07
- open_source: no [estimated], source: No public GitHub org found for refresh.dev as of 2026-06-07; no open-source product on https://www.refresh.dev/ accessed 2026-06-07
- license: unknown [unknown]
- deployment_model: unknown [unknown]
- maturity: private beta [estimated], source: https://www.ycombinator.com/companies/refresh accessed 2026-06-07 (early-stage YC X25; partners directly with frontier labs; no self-serve GA product visible)
- notable_customers: Frontier AI labs (unnamed) (self-claimed, frontier-lab tie) [reported], source: https://www.refresh.dev/ accessed 2026-06-07 (self-described partnerships with 'frontier labs and enterprises'); https://www.ycombinator.com/launches/Ncy-refresh-turning-real-work-into-rl-training-grounds accessed 2026-06-07 (self-claimed). No specific customer named or third-party verified.
- sources:
  - https://www.refresh.dev/ (accessed 2026-06-07)
  - https://www.withrefresh.com/ (accessed 2026-06-07)
  - https://www.refresh.dev/careers (accessed 2026-06-07)
  - https://www.ycombinator.com/companies/refresh (accessed 2026-06-07)
  - https://www.ycombinator.com/launches/Ncy-refresh-turning-real-work-into-rl-training-grounds (accessed 2026-06-07)
  - https://www.linkedin.com/company/refresh-dot-dev (accessed 2026-06-07)
  - https://www.linkedin.com/in/erikquintanilla/ (accessed 2026-06-07)
  - https://www.linkedin.com/in/christopher-settles (accessed 2026-06-07)

## Vmax, rank #21
- slug: vmax
- segment: Commercial vendors
- website: https://vmax.ai/
- focus_areas: Coding, Long-Horizon
- positioning: Vmax is a San Francisco reinforcement-learning startup (founded 2025 by three RL/robotics PhDs from UCL and UPenn) that automates the conversion of proprietary data and evals into RL environments for LLM-based agents, targeting long-horizon and coding tasks. Its public research includes unix-ctf, a procedural generator of capture-the-flag tasks for Unix/shell competence.
- best_fit: Teams needing custom, research-grade RL environments to train coding and long-horizon shell/terminal agents from proprietary data.
- overall_confidence: medium
- founded_year: 2025 [reported], source: https://www.southparkcommons.com/companies/vmax/ (accessed 2026-06-07); corroborated by PitchBook (https://pitchbook.com/profiles/company/907262-38) and search aggregators, no primary incorporation record reviewed
- status: active [confirmed], source: https://vmax.ai/ (accessed 2026-06-07); https://job-boards.greenhouse.io/vmax actively hiring (accessed 2026-06-07)
- hq_location: San Francisco, USA [reported], source: https://www.linkedin.com/company/vmax-ai (public snippet: Brannan St, San Francisco, CA 94107; accessed 2026-06-07); https://www.southparkcommons.com/companies/vmax/
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown], source: All 8 Greenhouse roles are listed San Francisco (https://job-boards.greenhouse.io/vmax), suggests onsite/SF-based, but remote policy not stated
- current_headcount: ~11 (LinkedIn 'all 11 employees' link, 2026-06-07); official LinkedIn size band 2-10 [reported], source: https://www.linkedin.com/company/vmax-ai (accessed 2026-06-07). Note: one search source cited ~5 employees, so exact count is uncertain
- headcount_band: 1-10 [estimated], source: https://www.linkedin.com/company/vmax-ai (accessed 2026-06-07), official size band '2-10 employees'; ~11 surfaced via profile but within small-team range
- headcount_growth: unknown [unknown]
- open_roles_count: 8 [confirmed], source: https://job-boards.greenhouse.io/vmax (accessed 2026-06-07), 8 roles, all San Francisco: MTS Applied RL, MTS Mechanistic Interpretability, MTS Open Endedness, MTS RL Algorithms, MTS RL Infrastructure, Open Application, Research Fellowship Mechanistic Interpretability, Research Fellowship Open Endedness
- has_researchers: yes [confirmed], source: https://vmax.ai/ (accessed 2026-06-07), founders are RL PhDs; unix-ctf paper (arXiv:2605.29115) authored by Vmax-affiliated researchers; multiple research/MTS roles open
- researcher_count: Small research-led team (~11 total). 3 co-founders are RL/robotics PhDs; named researchers from unix-ctf paper: Geoffrey Bradway, Roger Creus Castanyer, Lorenz Wolf [reported], source: https://www.linkedin.com/company/vmax-ai (accessed 2026-06-07); https://arxiv.org/abs/2605.29115 (author list)
- researcher_backgrounds: Matthew Sargent, RL PhD, University College London (2019-2024); co-founder; Augustine Mavor-Parker, RL PhD, University College London; CTO; previously Redwood Research (AI safety), Cold Spring Harbor Laboratory (NeuroAI), Illumina (AI for genomics); Heejin Jeong, PhD in ESE/robotics, University of Pennsylvania (GRASP Lab, 2020); co-founder; off-policy TD learning for robotics/autonomous systems; Founding team described on vmax.ai as 3 RL PhDs from UCL and UPenn with publications at NeurIPS, ICML, AAAI [reported], source: https://uk.linkedin.com/in/matthewjsargent ; https://www.linkedin.com/in/augustine-mavor-parker/ ; https://www.grasp.upenn.edu/people/heejin-jeong/ ; https://repository.upenn.edu/edissertations/3836/ ; https://vmax.ai/ ; https://www.southparkcommons.com/companies/vmax/ (accessed 2026-06-07)
- published_papers_or_benchmarks: unix-ctf: Procedural Environments for Unix-Competence Reinforcement Learning, arXiv:2605.29115 (https://arxiv.org/abs/2605.29115); procedural generator of CTF tasks for shell agents (656 portable variants); authors include Geoffrey Bradway, Roger Creus Castanyer, Lorenz Wolf; Collaboration releasing ~1k JavaScript coding tasks in Harbor format (with Martian/ARES, compatible with the Terminal-Bench ecosystem) [confirmed], source: https://arxiv.org/abs/2605.29115 ; https://withmartian.com/post/ares-open-source-infrastructure-for-online-rl-on-coding-agents (accessed 2026-06-07)
- total_raised: unknown [unknown], source: No disclosed amount on PitchBook (https://pitchbook.com/profiles/company/907262-38), Crunchbase, or press as of 2026-06-07, funding unannounced/undisclosed
- last_round: unknown [unknown], source: No round stage/date disclosed publicly as of 2026-06-07
- notable_investors: Race Capital; South Park Commons [reported], source: https://www.southparkcommons.com/companies/vmax/ (SPC self-lists as backer); PitchBook lists Race Capital and South Park Commons (accessed 2026-06-07), backers named, round/amount undisclosed
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown], source: No trust/security page found as of 2026-06-07
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: environments [confirmed], source: https://vmax.ai/ (accessed 2026-06-07), reinforcement learning company converting proprietary data and evals into RL environments for long-horizon LLM-agent tasks
- open_source: no [estimated], source: https://vmax.ai/ (accessed 2026-06-07), no public OSS product repo identified; unix-ctf released as a research paper (arXiv:2605.29115), not a maintained product repo
- license: unknown [unknown]
- deployment_model: unknown [unknown]
- maturity: unknown [unknown], source: Early-stage (founded 2025); no GA product page or pricing found as of 2026-06-07
- notable_customers: Martian / ARES team (withmartian), partnership: jointly releasing ~1k JavaScript coding tasks in the Harbor format (Harbor = Terminal-Bench task format) (self-claimed) [reported], source: https://withmartian.com/post/ares-open-source-infrastructure-for-online-rl-on-coding-agents (accessed 2026-06-07), described as a partnership/collaboration, not a confirmed paying customer. (Draft incorrectly attributed this to 'Harbor / Laude Institute'; the releasing partner is Martian/ARES.)
- sources:
  - https://vmax.ai/ (accessed 2026-06-07)
  - https://job-boards.greenhouse.io/vmax (accessed 2026-06-07)
  - https://www.linkedin.com/company/vmax-ai (accessed 2026-06-07)
  - https://www.linkedin.com/in/augustine-mavor-parker/ (accessed 2026-06-07)
  - https://www.linkedin.com/in/matthewjsargent/ (accessed 2026-06-07)
  - https://www.southparkcommons.com/companies/vmax/ (accessed 2026-06-07)
  - https://arxiv.org/abs/2605.29115 (accessed 2026-06-07)
  - https://withmartian.com/post/ares-open-source-infrastructure-for-online-rl-on-coding-agents (accessed 2026-06-07)
  - https://newsletter.semianalysis.com/p/rl-environments-and-rl-for-science (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/907262-38 (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/vmax (accessed 2026-06-07)
  - https://x.com/MavorParker/status/1868009967518880183 (accessed 2026-06-07)

## Andromede, rank #22
- slug: andromede
- segment: Commercial vendors
- website: https://andromede.ai/
- focus_areas: Long-Horizon
- positioning: Andromede is an early-stage RL data lab that programmatically generates RL environments, tasks, and verifiers from real-world data for post-training and evaluation of frontier agents, with an emphasis on long-horizon sequential reasoning tasks. As of mid-2026 it is in private beta, working with a small set of partners. It was co-founded by Guillaume Allegre (Founder & President) and Alexandre Sallinen (an EPFL-affiliated researcher who contributed to the Meditron medical-LLM project), and is backed by Unusual Ventures.
- best_fit: Buyers needing custom RL environments and verifiers derived from real-world data for post-training/evaluating long-horizon agentic models.
- overall_confidence: low
- founded_year: 2025 [reported], source: https://pitchbook.com/profiles/company/1158131-35 (search snippet; PitchBook page returns HTTP 403, accessed 2026-06-07); corroborated by https://www.unusual.vc/portfolio/ (accessed 2026-06-07)
- status: active [confirmed], source: https://andromede.ai/ (accessed 2026-06-07)
- hq_location: Lausanne, Switzerland [reported], source: https://pitchbook.com/profiles/company/1158131-35 (search snippet; page returns HTTP 403, accessed 2026-06-07)
- other_locations: New York, USA (founder/president Guillaume Allegre is LinkedIn-listed as New York-based; no confirmed office) [estimated], source: https://www.linkedin.com/in/guillaume-allegre/ (search snippet, accessed 2026-06-07)
- distributed_remote: yes [estimated], source: Co-founders are split across Lausanne (Sallinen/EPFL) and New York (Allegre per LinkedIn), suggesting a distributed team; not explicitly stated (accessed 2026-06-07)
- current_headcount: 2-10 employees (LinkedIn size band); PitchBook snippet states ~2 total employees, as of 2026-06-07 [reported], source: https://www.linkedin.com/company/andromedeai ; https://pitchbook.com/profiles/company/1158131-35 (search snippet, accessed 2026-06-07)
- headcount_band: 1-10 [reported], source: https://www.linkedin.com/company/andromedeai (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: https://andromede.ai/careers returns HTTP 404; no LinkedIn jobs visible (accessed 2026-06-07)
- has_researchers: yes [reported], source: Co-founder Alexandre Sallinen is an EPFL-affiliated researcher (contributor to the Meditron medical-LLM project; Google Scholar profile); GitHub org self-describes as 'Research Data Lab focused on RL environment generation', https://scholar.google.com/citations?user=-ajWSEcAAAAJ ; https://github.com/Andromede-AI (accessed 2026-06-07)
- researcher_count: ~1 (co-founder Alexandre Sallinen, an EPFL/Meditron researcher); no public team page to confirm others [estimated], source: https://www.linkedin.com/in/alexandre-sallinen-033359294/ ; https://scholar.google.com/citations?user=-ajWSEcAAAAJ (accessed 2026-06-07)
- researcher_backgrounds: Alexandre Sallinen (co-founder) - EPFL; contributor to the Meditron open-source medical LLM project; RL/LLM research background; Guillaume Allegre (co-founder & president) - ex-BCG X; MIT (Machine Learning & Operations Research), engineering/applied mathematics [reported], source: https://www.linkedin.com/in/alexandre-sallinen-033359294/ ; https://www.linkedin.com/in/guillaume-allegre/ ; https://scholar.google.com/citations?user=-ajWSEcAAAAJ (search snippets, accessed 2026-06-07)
- published_papers_or_benchmarks: unknown [unknown], source: No Andromede-branded papers or benchmarks found; co-founder Sallinen's research (e.g. Meditron) predates and is separate from the company (accessed 2026-06-07)
- total_raised: unknown [unknown], source: No disclosed funding figure found; PitchBook funding data paywalled (accessed 2026-06-07)
- last_round: unknown [unknown], source: No round stage/amount/date disclosed; PitchBook funding data paywalled (HTTP 403), accessed 2026-06-07
- notable_investors: Unusual Ventures [reported], source: https://www.unusual.vc/portfolio/ (Andromede listed in Unusual Ventures' own portfolio page, accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown], source: Site lists a security@andromede.ai contact but no SOC 2 / trust page found (accessed 2026-06-07)
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: No /security or /trust page found; only security@andromede.ai contact listed (accessed 2026-06-07)
- what_they_sell: environments [confirmed], source: https://andromede.ai/ (accessed 2026-06-07)
- open_source: no [reported], source: https://github.com/Andromede-AI states 'This organization has no public repositories' (accessed 2026-06-07)
- license: unknown [unknown]
- deployment_model: unknown [unknown]
- maturity: private beta [confirmed], source: https://andromede.ai/ (accessed 2026-06-07)
- notable_customers: unknown [unknown], source: Site states it works with 'a small set of partners' but names none (accessed 2026-06-07)
- sources:
  - https://andromede.ai/ (accessed 2026-06-07)
  - https://www.linkedin.com/company/andromedeai (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/1158131-35 (accessed 2026-06-07)
  - https://github.com/Andromede-AI (accessed 2026-06-07)
  - https://alignlist.com/guides/top-40-rl-environments-startups-and-companies (accessed 2026-06-07)
  - https://aimultiple.com/rl-environments (accessed 2026-06-07)
  - https://andromede.ai/careers (accessed 2026-06-07)

## Plato, rank #23
- slug: plato
- segment: Commercial vendors
- website: https://plato.so
- focus_areas: Computer Use, Enterprise Workflows
- positioning: Plato (plato.so, Plato Technologies, Inc.) builds simulated worlds for training and evaluating browser and computer-use agents, recreating real websites/software (e.g. Amazon/Airbnb/Gmail-style replicas) as reinforcement-learning environments with structured APIs for interaction, state tracking and scoring. It also offers a 'Computer Use' capability driving a full Linux desktop, positioning at the intersection of browser interaction and enterprise workflow simulation.
- best_fit: AI labs/teams needing high-fidelity replica web/enterprise environments to train and evaluate browser and computer-use agents via RL.
- overall_confidence: low
- founded_year: 2025 [reported], source: PitchBook 'Plato (United States)' and Crunchbase (plato-379d / plato-d5c7) snippets, accessed 2026-06-07
- status: active [confirmed], source: https://plato.so 2026-06-07; NYT/Cade Metz coverage Dec 2025 via https://theoutpost.ai/news-story/silicon-valley-startups-clone-amazon-and-gmail-to-train-ai-agents-on-complex-tasks-22091/ 2026-06-07
- hq_location: San Francisco, CA, USA [reported], source: PitchBook/Crunchbase snippets accessed 2026-06-07; founders' LinkedIn list San Francisco
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: ~10 employees [estimated], source: PitchBook/Wellfound search snippets (US Plato) accessed 2026-06-07; not directly confirmed via LinkedIn public snippet
- headcount_band: 1-10 [estimated], source: PitchBook snippets cite ~10 total employees; consistent with seed/pre-seed-stage startup, accessed 2026-06-07
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown]
- has_researchers: yes [estimated], source: Co-founder/CTO Pranav Putta has AI research background (MultiOn, Georgia Tech); LinkedIn snippets accessed 2026-06-07
- researcher_count: unknown [unknown]
- researcher_backgrounds: Pranav Putta (Co-founder/CTO), prior MultiOn, Georgia Institute of Technology, Tonic.ai; Robert Farlow (Co-founder/CEO) [reported], source: LinkedIn public snippets for Pranav Putta (in/pranav-putta-3512b47a) and Robert Farlow (in/robfarlow), accessed 2026-06-07
- published_papers_or_benchmarks: unknown [unknown]
- total_raised: unknown [unknown], source: No plato.so-specific funding amount disclosed. Widely circulated $21M/$14.5M/$6.5M figures belong to an unrelated Berlin wholesale-AI Plato; £260k belongs to an unrelated UK edtech Plato. Crunchbase lists US browser-agents Plato as Pre-Seed only with no disclosed amount, accessed 2026-06-07
- last_round: Pre-Seed (amount and date not disclosed) [reported], source: Crunchbase (plato-379d / plato-d5c7) lists the US browser-agents Plato at Pre-Seed stage; no amount/date found, accessed 2026-06-07
- notable_investors: unknown [unknown], source: No verified investors for plato.so. Do not confuse with Berlin Plato (Atomico/Cherry Ventures) or UK edtech Plato (SFC Capital), accessed 2026-06-07
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: environments [confirmed], source: https://docs.plato.so 2026-06-07; Crunchbase 'Evals & datasets for web agents' snippet 2026-06-07
- open_source: no [estimated], source: https://plato.so 2026-06-07; https://docs.plato.so 2026-06-07, hosted platform with proprietary Python SDK (plato-sdk-v2), no public OSS repo identified
- license: unknown [unknown]
- deployment_model: managed-hosted (SaaS at plato.so with dedicated tenant nodes at {tenant}.plato.so) plus API/Python SDK access [confirmed], source: https://docs.plato.so 2026-06-07
- maturity: unknown [unknown]
- notable_customers: unknown [unknown], source: NYT (Cade Metz, Dec 2025) names OpenAI/Google/Amazon/Anthropic as users of the replica-website RL technique generally, but does not name them as Plato's confirmed customers; no named, verified Plato customer found, accessed 2026-06-07
- sources:
  - https://plato.so/ (accessed 2026-06-07)
  - https://docs.plato.so (accessed 2026-06-07)
  - https://www.linkedin.com/in/robfarlow/ (accessed 2026-06-07)
  - https://www.linkedin.com/in/pranav-putta-3512b47a (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/plato-379d (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/752634-64 (accessed 2026-06-07)
  - https://tracxn.com/d/companies/plato/__f-KUHjIqU9_tRivtPsI5QjHBWL3AFdLMphYurLed-uw/funding-and-investors (accessed 2026-06-07)
  - https://wellfound.com/company/platoteam/people (accessed 2026-06-07)
  - https://theoutpost.ai/news-story/silicon-valley-startups-clone-amazon-and-gmail-to-train-ai-agents-on-complex-tasks-22091/ (accessed 2026-06-07)
  - https://www.techmeme.com/251203/p10 (accessed 2026-06-07)
  - https://alignlist.com/guides/top-40-rl-environments-startups-and-companies (accessed 2026-06-07)
  - https://podcasts.apple.com/us/podcast/robert-farlow-from-plato/id1634787423?i=1000740840151 (accessed 2026-06-07)
  - https://www.eu-startups.com/2026/02/from-germany-for-the-world-plato-secures-e12-2-million-to-automate-sales-and-erp-workflows-in-distribution/ (accessed 2026-06-07)

## AIChamp, rank #24
- slug: aichamp
- segment: Commercial vendors
- website: https://aichamp.com/
- focus_areas: Enterprise Workflows, Long-Horizon
- positioning: AIChamp builds custom reinforcement-learning environments and 'Virtual Gym' simulations for training and evaluating tool-using AI agents on long-horizon, multi-step enterprise tasks, pairing engineered environments (agents operating in software like Slack, Notion, Linear) with domain experts who design and grade tasks (SFT/RLHF/process supervision). The company emphasizes deep industry authority and expert-sourced data, having pivoted from a remote-talent/hiring marketplace background.
- best_fit: Buyers needing expert-graded, long-horizon enterprise-workflow RL environments where agents operate inside real business tools (Slack, Notion, Linear).
- overall_confidence: low
- founded_year: unknown [unknown], source: Conflicting: LinkedIn (https://www.linkedin.com/company/aichamp-finds-a-players) shows founded 2025; Tracxn (https://tracxn.com/d/companies/aichamp) lists 'Founded Year 2022', not reliably confirmed, accessed 2026-06-07
- status: active [confirmed], source: https://aichamp.com/ (accessed 2026-06-07); blog post dated 2026-02-04
- hq_location: San Francisco, USA (CEO-based; reported, not officially confirmed; Tracxn alternatively lists Bali, Indonesia) [reported], source: Search snippets referencing CEO location (San Francisco) and Tracxn profile listing Bali, Indonesia, conflicting; not confirmed on official site, accessed 2026-06-07
- other_locations: unknown [unknown]
- distributed_remote: yes [reported], source: https://torre.ai/teams/AIChamp (accessed 2026-06-07) lists roles as Remote (anywhere); company sources global experts; CEO SF / Tracxn Bali suggests distributed footprint
- current_headcount: ~2-10 (as of 2026-06-07) [estimated], source: https://www.linkedin.com/company/aichamp-finds-a-players public snippet shows '2-10 employees'; https://theorg.com/org/aichamp lists 5 named members in '1-10' band; https://torre.ai/teams/AIChamp shows 11 members, accessed 2026-06-07
- headcount_band: 1-10 [estimated], source: LinkedIn '2-10 employees' and TheOrg '1-10' band (5 named members), accessed 2026-06-07. Note: Torre shows 11 (likely incl. non-employee/expert contributors)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: Torre shows 2 jobs posted, both closed (accessed 2026-06-07); app.aichamp.com lists recruiting expert-trainer roles but count not reliably enumerable
- has_researchers: unknown [unknown], source: Team described as 'alumni of OpenAI and xAI team' on own site (self-claimed); no named, verifiable research staff confirmed, accessed 2026-06-07
- researcher_count: unknown [unknown]
- researcher_backgrounds: Self-claimed 'alumni of OpenAI and xAI team' (vendor site, unverified); CEO/founder Vol Goloshuk previously founded BrightestMinds lead-generation / sales-development agency (reported); Mati Roy listed as CTO (per LinkedIn title / TheOrg roster) [reported], source: https://aichamp.com/ (self-claimed alumni); https://theorg.com/org/aichamp roster; LinkedIn profiles for Goloshuk and Roy, accessed 2026-06-07
- published_papers_or_benchmarks: unknown [unknown], source: No papers or benchmarks published by AIChamp found; only company blog posts, accessed 2026-06-07
- total_raised: $0 / no funding raised [reported], source: https://tracxn.com/d/companies/aichamp ('aiChamp has not raised any funding rounds yet') and search snippet describing it as 'an unfunded company', accessed 2026-06-07
- last_round: none [reported], source: https://tracxn.com/d/companies/aichamp, no funding rounds, accessed 2026-06-07
- notable_investors: unknown [reported], source: https://tracxn.com/d/companies/aichamp, no investors listed (unfunded), accessed 2026-06-07
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown], source: No security/trust page found (aichamp.com/security returns 404), accessed 2026-06-07
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: https://aichamp.com/security/ returns HTTP 404, accessed 2026-06-07
- what_they_sell: mixed [confirmed], source: https://aichamp.com/ (accessed 2026-06-07), custom RL environments / simulations ('Virtual Gyms') plus expert-sourced human data (SFT/RLHF/process supervision); experts recruited via 'Sniper Sourcing'
- open_source: no [estimated], source: No public repos or OSS offering found as of 2026-06-07
- license: unknown [unknown]
- deployment_model: unknown [unknown], source: Described as service-based engagements with custom environments; specific deployment model not officially stated, accessed 2026-06-07
- maturity: unknown [unknown], source: No GA/beta/preview status stated; appears early-stage and operational, accessed 2026-06-07
- notable_customers: unknown [unknown], source: No customer logos or names disclosed on official site; no third-party customer confirmation found, accessed 2026-06-07
- sources:
  - https://aichamp.com/ (accessed 2026-06-07)
  - https://aichamp.com/blog/ (accessed 2026-06-07)
  - https://aichamp.com/security/ (accessed 2026-06-07)
  - https://www.linkedin.com/company/aichamp-finds-a-players (accessed 2026-06-07)
  - https://www.linkedin.com/in/goloshuk/ (accessed 2026-06-07)
  - https://www.linkedin.com/in/matiroy/ (accessed 2026-06-07)
  - https://torre.ai/teams/AIChamp (accessed 2026-06-07)
  - https://theorg.com/org/aichamp (accessed 2026-06-07)
  - https://app.aichamp.com/apply/jobs (accessed 2026-06-07)

## Habitat Inc, rank #25
- slug: habitat-inc
- segment: Commercial vendors
- website: https://www.habitat.inc/
- focus_areas: Coding, Computer Use, Enterprise Workflows
- positioning: Habitat Inc is an early-stage commercial vendor (2-10 employees, New York HQ) building reinforcement-learning environments for white-collar / work automation, with stated focus on code and desktop-style (computer use) interaction tasks for training agentic AI models. It appears in third-party listings of RL-environment suppliers serving AI labs. No funding, customer, or certification information is publicly available.
- best_fit: Buyers needing RL environments that simulate enterprise/desktop and coding workflows to post-train computer-use and coding agents.
- overall_confidence: low
- founded_year: unknown [unknown]
- status: active [reported], source: https://www.linkedin.com/company/habitat-ai-inc (accessed 2026-06-07); https://www.habitat.inc/ (accessed 2026-06-07)
- hq_location: New York, NY, USA [reported], source: https://www.linkedin.com/company/habitat-ai-inc (accessed 2026-06-07), public page lists address 116 E 30th St, New York, NY 10016
- other_locations: unknown [unknown], source: SF was inferred from a single founder LinkedIn profile location (https://www.linkedin.com/in/maximenis/, accessed 2026-06-07); insufficient to assert a company office, downgraded to unknown
- distributed_remote: unknown [unknown]
- current_headcount: 2-10 (approx 5 associated on LinkedIn) [reported], source: https://www.linkedin.com/company/habitat-ai-inc (accessed 2026-06-07)
- headcount_band: 1-10 [reported], source: https://www.linkedin.com/company/habitat-ai-inc (accessed 2026-06-07), '2-10 employees'
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown]
- has_researchers: unknown [unknown]
- researcher_count: unknown [unknown]
- researcher_backgrounds: Maxim Enis (co-founder), Williams College '24; prior Ramp association per LinkedIn; co-author (with Mark Hopkins, Williams) of arXiv:2404.13813 'From LLM to NMT: Advancing Low-Resource Machine Translation with Claude' (2024, academic, predates company); Andrew Megalaa (co-founder), Williams College '24 [reported], source: https://www.linkedin.com/in/maximenis/ (accessed 2026-06-07); https://arxiv.org/abs/2404.13813 (accessed 2026-06-07); https://www.instagram.com/p/C6ra5D1PrGo/ (accessed 2026-06-07)
- published_papers_or_benchmarks: unknown [unknown], source: No company-published papers or benchmarks found. Co-founder M. Enis authored arXiv:2404.13813 academically prior to Habitat; not attributed to the company
- total_raised: unknown [unknown], source: No Crunchbase/press/announcement found for habitat.inc as of 2026-06-07; Crunchbase 'Habitat' hits are unrelated entities
- last_round: unknown [unknown]
- notable_investors: unknown [unknown]
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: environments [reported], source: https://www.linkedin.com/company/habitat-ai-inc (accessed 2026-06-07), 'RL environments for white-collar work'; https://alignlist.com/guides/top-40-rl-environments-startups-and-companies (accessed 2026-06-07); https://www.chemistry.vc/post/rl-reigns-supreme (accessed 2026-06-07)
- open_source: no [estimated], source: No public GitHub org or OSS repos found for habitat.inc as of 2026-06-07
- license: unknown [unknown]
- deployment_model: unknown [unknown]
- maturity: unknown [unknown]
- notable_customers: unknown [unknown]
- sources:
  - https://www.habitat.inc/ (accessed 2026-06-07)
  - https://www.linkedin.com/company/habitat-ai-inc (accessed 2026-06-07)
  - https://www.linkedin.com/in/maximenis/ (accessed 2026-06-07)
  - https://www.linkedin.com/in/andrewmegalaa/ (accessed 2026-06-07)
  - https://www.instagram.com/p/C6ra5D1PrGo/ (accessed 2026-06-07)
  - https://alignlist.com/guides/top-40-rl-environments-startups-and-companies (accessed 2026-06-07)
  - https://newsletter.semianalysis.com/p/rl-environments-and-rl-for-science (accessed 2026-06-07)
  - https://www.chemistry.vc/post/rl-reigns-supreme (accessed 2026-06-07)

## Scale AI (not ranked, incumbent / infrastructure / open-source)
- slug: scale-ai
- segment: Incumbents also building RL environments
- website: https://scale.com
- focus_areas: Coding, Computer Use, Enterprise Workflows, Long-Horizon
- positioning: Scale AI is the data-labeling and AI-data incumbent that has extended into RL environments, offering simulated web apps, macOS/Windows-like desktop VMs, and MCP-tool environments (Slack, HubSpot, Linear) with expert-designed objectives, rubrics, and automated verifiers to train and evaluate agents on long-horizon professional workflows. Following Meta's ~$14.3B June 2025 investment (~49% non-voting stake) and founder Alexandr Wang's departure to Meta, several frontier-lab customers (OpenAI, Google, xAI) reportedly scaled back or paused engagement over conflict-of-interest concerns.
- best_fit: Enterprises and government buyers (and labs without a Meta conflict concern) wanting an established, security-certified vendor to supply expert-built, verifiable RL environments and human data for agent training across coding, computer-use, browser, and enterprise-tool workflows.
- overall_confidence: medium
- founded_year: 2016 [confirmed], source: https://en.wikipedia.org/wiki/Scale_AI (accessed 2026-06-07); founded 2016 by Alexandr Wang and Lucy Guo via Y Combinator
- status: active (independent; Meta holds ~49% non-voting minority stake as of June 2025) [confirmed], source: https://techcrunch.com/2025/06/13/scale-ai-confirms-significant-investment-from-meta-says-ceo-alexandr-wang-is-leaving/ (accessed 2026-06-07); https://www.cnbc.com/2025/11/04/scale-ais-life-after-meta-has-been-rocky-cfo-insists-not-a-zombie.html
- hq_location: San Francisco, California, USA [confirmed], source: https://scale.com/about (accessed 2026-06-07); https://en.wikipedia.org/wiki/Scale_AI
- other_locations: St. Louis, Missouri, USA (opened 2022) [reported], source: https://en.wikipedia.org/wiki/Scale_AI (accessed 2026-06-07)
- distributed_remote: unknown [unknown]
- current_headcount: ~1,000-1,200 (late 2025); reduced after July 2025 layoff of ~200 (14%) from a ~1,400 global FTE workforce, plus ~500 contractors cut [reported], source: https://techcrunch.com/2025/07/16/scale-ai-lays-off-14-of-staff-largely-in-data-labeling-business/ (accessed 2026-06-07); https://www.cnbc.com/2025/11/04/scale-ais-life-after-meta-has-been-rocky-cfo-insists-not-a-zombie.html (CFO references '1,000-plus person company')
- headcount_band: 200+ [confirmed], source: https://techcrunch.com/2025/07/16/scale-ai-lays-off-14-of-staff-largely-in-data-labeling-business/ (accessed 2026-06-07); multiple sources cite ~1,000-1,400 FTE
- headcount_growth: ~14% FTE reduction in July 2025 (~200 cut from ~1,400) plus ~500 contractors; interim CEO signaled intent to staff up enterprise and government sales units in H2 2025 [reported], source: https://techcrunch.com/2025/07/16/scale-ai-lays-off-14-of-staff-largely-in-data-labeling-business/ (accessed 2026-06-07)
- open_roles_count: unknown [unknown]
- has_researchers: yes [reported], source: https://en.wikipedia.org/wiki/Scale_AI (accessed 2026-06-07); Scale operates the SEAL research lab publishing model evaluations/leaderboards (not stated on scale.com/rlenvironments)
- researcher_count: unknown [unknown]
- researcher_backgrounds: unknown [unknown]
- published_papers_or_benchmarks: Scale operates the SEAL (Safety, Evaluations and Alignment Lab) research group publishing model evaluations and public leaderboards (e.g., Humanity's Last Exam, SEAL leaderboards) [reported], source: https://en.wikipedia.org/wiki/Scale_AI (accessed 2026-06-07); https://techcrunch.com/2025/09/21/silicon-valley-bets-big-on-environments-to-train-ai-agents/
- total_raised: ~$1.6B in disclosed equity rounds prior to Meta; Meta's June 2025 ~$14.3B was a strategic stake purchase (largely secondary/cash to existing holders), not a conventional primary funding round, so combining them into a single ~$15.9B 'raised' figure overstates capital raised [reported], source: https://techcrunch.com/2025/06/13/scale-ai-confirms-significant-investment-from-meta-says-ceo-alexandr-wang-is-leaving/ (accessed 2026-06-07); https://techcrunch.com/2024/05/21/data-labeling-startup-scale-ai-raises-1b-as-valuation-doubles-to-13-8b/
- last_round: Meta strategic investment, ~$14.3B for ~49% non-voting stake, June 2025 (valuing Scale at ~$29B); prior Series F ~$1B in May 2024 at ~$13.8B valuation [reported], source: https://techcrunch.com/2025/06/13/scale-ai-confirms-significant-investment-from-meta-says-ceo-alexandr-wang-is-leaving/ (accessed 2026-06-07); https://techcrunch.com/2024/05/21/data-labeling-startup-scale-ai-raises-1b-as-valuation-doubles-to-13-8b/
- notable_investors: Meta Platforms; Accel; Amazon; Nvidia; Founders Fund; Index Ventures; Tiger Global Management; Dragoneer Investment Group; Greenoaks; Y Combinator [reported], source: https://en.wikipedia.org/wiki/Scale_AI (accessed 2026-06-07); https://news.crunchbase.com/ai/scale-holistic-raise-big-accel-nvda-amzn/
- valuation: ~$29B (post Meta June 2025 investment) [reported], source: https://techcrunch.com/2025/06/13/scale-ai-confirms-significant-investment-from-meta-says-ceo-alexandr-wang-is-leaving/ (accessed 2026-06-07); corroborated by Bloomberg and multiple outlets
- revenue_signals: ~$870M revenue in 2024 (reported); company guided to ~$2B revenue for 2025 (Bloomberg, Apr 2025), vendor/forward guidance, not audited [reported], source: https://www.bloomberg.com/news/articles/2025-04-02/scale-ai-expects-to-more-than-double-sales-to-2-billion-in-2025 (accessed 2026-06-07); https://en.wikipedia.org/wiki/Scale_AI
- soc2: Type II [confirmed], source: https://scale.com/security (accessed 2026-06-07); page states 'SOC 2 Type II'; reports available via trust.scale.com
- other_certifications: ISO/IEC 27001:2022; FedRAMP High Authorized; DoD IL4 Provisional Authorization (DISA) [confirmed], source: https://scale.com/security (accessed 2026-06-07), HIPAA REMOVED: not listed on the current security page (page omits HIPAA); only verifiable via separate older blog claim
- security_page: https://scale.com/security (Trust Center: https://trust.scale.com/) [confirmed], source: https://scale.com/security (accessed 2026-06-07)
- what_they_sell: mixed (human data / data labeling, RL environments, model evaluations, AI infrastructure / applications) [confirmed], source: https://scale.com/about (accessed 2026-06-07); https://scale.com/rlenvironments
- open_source: no [estimated], source: https://scale.com/rlenvironments (accessed 2026-06-07); offered as a commercial managed product, no OSS license indicated
- license: unknown [unknown]
- deployment_model: managed-hosted (vendor-operated environments/infrastructure to run agent training and evaluation; simulated APIs, MCP servers, GUIs) [reported], source: https://scale.com/rlenvironments (accessed 2026-06-07)
- maturity: GA (RL Environments product publicly offered) [reported], source: https://scale.com/rlenvironments (accessed 2026-06-07); https://techcrunch.com/2025/09/21/silicon-valley-bets-big-on-environments-to-train-ai-agents/
- notable_customers: OpenAI (former / winding down work after Meta deal) (verified, frontier-lab tie); Google / Alphabet (former / cutting ties after Meta deal; reportedly Scale's largest customer) (verified, frontier-lab tie); xAI (reportedly paused work after Meta deal; press-reported, not firmly confirmed) (self-claimed, frontier-lab tie); Microsoft (press-reported customer; relationship reportedly affected post-deal, not firmly confirmed) (self-claimed); U.S. Department of Defense (verified); General Motors (verified) [reported], source: https://fortune.com/2025/06/19/openai-is-phasing-out-scale-ai-work-following-startups-meta-deal/ (accessed 2026-06-07); https://www.cnbc.com/2025/11/04/scale-ais-life-after-meta-has-been-rocky-cfo-insists-not-a-zombie.html, NOTE: OpenAI, Google, and xAI reported winding down/pausing work post-Meta deal; Meta REMOVED from customer list (it is now a ~49% investor/competitor, not appropriately a current customer)
- sources:
  - https://scale.com/rlenvironments (accessed 2026-06-07)
  - https://scale.com/blog/rl-environments (accessed 2026-06-07)
  - https://scale.com/about (accessed 2026-06-07)
  - https://scale.com/security (accessed 2026-06-07)
  - https://scale.com/blog/soc2-hipaa (accessed 2026-06-07)
  - https://scale.com/blog/scale-ai-announces-next-phase-of-company-evolution (accessed 2026-06-07)
  - https://techcrunch.com/2025/06/13/scale-ai-confirms-significant-investment-from-meta-says-ceo-alexandr-wang-is-leaving/ (accessed 2026-06-07)
  - https://techcrunch.com/2025/09/21/silicon-valley-bets-big-on-environments-to-train-ai-agents/ (accessed 2026-06-07)
  - https://www.cnbc.com/2025/07/16/scale-ai-cuts-14percent-of-workforce-after-meta-investment-hiring-of-wang.html (accessed 2026-06-07)
  - https://techcrunch.com/2024/05/21/data-labeling-startup-scale-ai-raises-1b-as-valuation-doubles-to-13-8b/ (accessed 2026-06-07)
  - https://news.crunchbase.com/ai/scale-holistic-raise-big-accel-nvda-amzn/ (accessed 2026-06-07)
  - https://en.wikipedia.org/wiki/Scale_AI (accessed 2026-06-07)
  - https://www.linkedin.com/company/scaleai (accessed 2026-06-07)
  - https://fortune.com/2025/06/14/self-made-billionaire-college-dropout-alexandr-wang-signs-14-3-billion-deal-to-bolster-metas-ai-efforts-theres-a-huge-premium-to-naivete/ (accessed 2026-06-07)

## Modal (not ranked, incumbent / infrastructure / open-source)
- slug: modal
- segment: Adjacent: execution infrastructure
- website: https://modal.com
- focus_areas: Coding
- positioning: Modal (Modal Labs) is a New York-based, Python-native serverless cloud purpose-built for AI/ML workloads, providing on-demand GPU/CPU compute, fast-booting sandboxed containers, inference, fine-tuning, and code execution. It is execution infrastructure rather than an RL-environment vendor, but is used to run reinforcement-learning training and large fleets of parallel sandboxed environments for AI labs.
- best_fit: Buyers needing serverless, autoscaling compute to run untrusted code, RL training loops, and thousands of parallel sandboxed agent/coding environments without managing infrastructure.
- overall_confidence: high
- founded_year: 2021 [confirmed], source: https://techcrunch.com/2026/02/11/ai-inference-startup-modal-labs-in-talks-to-raise-at-2-5b-valuation-sources-say/ ; founded Jan 2021 corroborated by startupintros.com / Sacra (accessed 2026-06-07)
- status: active [confirmed], source: https://modal.com/blog/modal-series-c (accessed 2026-06-07)
- hq_location: New York, NY, USA [confirmed], source: https://modal.com/company (accessed 2026-06-07)
- other_locations: San Francisco, CA, USA; Stockholm, Sweden [confirmed], source: https://modal.com/company ; https://modal.com/blog/modal-series-c (accessed 2026-06-07)
- distributed_remote: yes [estimated], source: https://modal.com/company (accessed 2026-06-07), three offices (NYC, SF, Stockholm) with roles spanning all locations
- current_headcount: 120+ team members (official Series C blog, May 2026); ~153 employees per LinkedIn/Tracxn snippet (as of April 2026) [reported], source: https://modal.com/blog/modal-series-c (120+); LinkedIn https://www.linkedin.com/company/modal-labs and Tracxn ~153 (accessed 2026-06-07)
- headcount_band: 51-200 [confirmed], source: LinkedIn/Tracxn ~153 employees ; https://modal.com/blog/modal-series-c (120+) (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: 30+ open roles across NYC, SF, Stockholm [reported], source: https://modal.com/company (accessed 2026-06-07)
- has_researchers: no [estimated], source: https://modal.com/company (accessed 2026-06-07), infrastructure/engineering company; no research division advertised, though founders/engineers have strong ML backgrounds
- researcher_count: unknown [unknown]
- researcher_backgrounds: CEO Erik Bernhardsson: ex-Spotify (music recommendations), ex-CTO Better.com, creator of open-source Annoy and Luigi; CTO Akshat Bubna: ex-Scale AI engineer, MIT [reported], source: https://erikbern.com/about.html ; https://techcrunch.com/2026/02/11/ai-inference-startup-modal-labs-in-talks-to-raise-at-2-5b-valuation-sources-say/ ; startupintros.com founder profiles (accessed 2026-06-07)
- published_papers_or_benchmarks: unknown [unknown]
- total_raised: ~$466M total disclosed [reported], source: https://modal.com/company ; corroborated by Sacra and startupintros.com (accessed 2026-06-07)
- last_round: Series C, $355M, closed ~2026-05-21 [confirmed], source: https://modal.com/blog/modal-series-c ; https://siliconangle.com/2026/05/21/serverless-ai-infrastructure-startup-modal-labs-seals-355m-funding-round/ ; https://www.datacenterdynamics.com/en/news/modal-labs-secures-funding/ ; https://www.finsmes.com/2026/05/modal-raises-355m-in-series-c-funding-at-post-money-valuation-of-4-65-billion.html (accessed 2026-06-07)
- notable_investors: General Catalyst (Series C co-lead); Redpoint Ventures (Series C co-lead; earlier Series A lead); Lux Capital (earlier round lead); Amplify Partners; Menlo Ventures; Bain Capital Ventures; Accel [confirmed], source: https://modal.com/blog/modal-series-c ; corroborated by DCD, SiliconANGLE, Tech Startups (accessed 2026-06-07)
- valuation: $4.65B post-money (Series C, May 2026); first tranche priced at $2.5B, second at $4.65B; up from $1.1B (Series B) [confirmed], source: https://modal.com/blog/modal-series-c ; https://www.datacenterdynamics.com/en/news/modal-labs-secures-funding/ ; https://www.finsmes.com/2026/05/modal-raises-355m-in-series-c-funding-at-post-money-valuation-of-4-65-billion.html (accessed 2026-06-07)
- revenue_signals: ~$300M annualized revenue run rate (May 2026), grown ~5x since September; ~$50M ARR reported Feb 2026 [reported], source: https://modal.com/blog/modal-series-c ; https://www.datacenterdynamics.com/en/news/modal-labs-secures-funding/ ; https://techcrunch.com/2026/02/11/ai-inference-startup-modal-labs-in-talks-to-raise-at-2-5b-valuation-sources-say/ (accessed 2026-06-07)
- soc2: Type II [confirmed], source: https://modal.com/docs/guide/security (SOC 2 Type II audit completed; report via trust.modal.com) (accessed 2026-06-07)
- other_certifications: HIPAA: supports HIPAA-compliant workloads via BAA on Enterprise plan (no formal HIPAA certification exists); PCI handled via Stripe (Level 1) [confirmed], source: https://modal.com/docs/guide/security (accessed 2026-06-07)
- security_page: https://trust.modal.com (security portal); https://modal.com/docs/guide/security [confirmed], source: https://modal.com/docs/guide/security (accessed 2026-06-07)
- what_they_sell: infra [confirmed], source: https://modal.com/ (accessed 2026-06-07)
- open_source: no [confirmed], source: https://modal.com/ (accessed 2026-06-07), core serverless platform is proprietary/managed; only client SDKs are open source
- license: Client SDKs open source (Python client Apache-2.0, JS/TS/Go libmodal MIT, examples MIT); platform itself proprietary [confirmed], source: https://github.com/modal-labs/modal-client ; https://github.com/modal-labs/libmodal (accessed 2026-06-07)
- deployment_model: managed-hosted (serverless cloud); Python/JS/TS/Go SDKs and API [confirmed], source: https://modal.com/ ; https://github.com/modal-labs (accessed 2026-06-07)
- maturity: GA [confirmed], source: https://modal.com/ (accessed 2026-06-07)
- notable_customers: Cognition (Devin) (self-claimed); Applied Compute (self-claimed); Physical Intelligence (self-claimed); Suno (self-claimed); Ramp (self-claimed); DoorDash (self-claimed); Decagon (self-claimed); Chai Discovery (self-claimed); Reducto (self-claimed); Meta (Code World Models RL sandboxes) (self-claimed, frontier-lab tie) [reported], source: https://modal.com/blog/modal-series-c (DoorDash, Reducto, Cognition, Decagon, Ramp, Applied Compute, Physical Intelligence, Chai Discovery, Suno listed on vendor page, self-claimed); Meta/Code World Models usage also described in third-party CWM coverage (machine-learning-made-simple.medium.com, blog.promptlayer.com) (accessed 2026-06-07)
- sources:
  - https://modal.com/ (accessed 2026-06-07)
  - https://modal.com/company (accessed 2026-06-07)
  - https://modal.com/blog/modal-series-c (accessed 2026-06-07)
  - https://modal.com/blog/announcing-our-series-b (accessed 2026-06-07)
  - https://modal.com/blog/soc2type2 (accessed 2026-06-07)
  - https://modal.com/blog/hipaa (accessed 2026-06-07)
  - https://modal.com/docs/guide/security (accessed 2026-06-07)
  - https://techcrunch.com/2026/02/11/ai-inference-startup-modal-labs-in-talks-to-raise-at-2-5b-valuation-sources-say/ (accessed 2026-06-07)
  - https://www.datacenterdynamics.com/en/news/modal-labs-secures-funding/ (accessed 2026-06-07)
  - https://siliconangle.com/2026/05/21/serverless-ai-infrastructure-startup-modal-labs-seals-355m-funding-round/ (accessed 2026-06-07)
  - https://techstartups.com/2026/05/21/modal-labs-raises-355m-quadrupling-valuation-to-4-65b-as-ai-infrastructure-demand-surges/ (accessed 2026-06-07)
  - https://github.com/modal-labs (accessed 2026-06-07)
  - https://github.com/modal-labs/modal-client (accessed 2026-06-07)
  - https://erikbern.com/about.html (accessed 2026-06-07)
  - https://www.linkedin.com/company/modal-labs (accessed 2026-06-07)

## Mercor (not ranked, incumbent / infrastructure / open-source)
- slug: mercor
- segment: Incumbents also building RL environments
- website: https://www.mercor.com/
- focus_areas: Coding, Enterprise Workflows, Long-Horizon
- positioning: Mercor is a venture-backed expert-marketplace and AI-training-data company that organizes a network of ~30,000+ domain experts (doctors, lawyers, bankers, engineers) to produce RLHF data, evaluations, and reinforcement-learning environments for frontier AI labs and enterprises. Originally an AI-recruiting platform, it pivoted to human-data/RL services and expanded its RL-environment capability via the February 2026 acquisition of Sepal AI.
- best_fit: Buyers needing large-scale, expert-validated human data, professional-domain evals, and RL environments staffed quickly through an established contractor network.
- overall_confidence: high
- founded_year: 2023 [confirmed], source: https://en.wikipedia.org/wiki/Mercor (accessed 2026-06-07); corroborated by https://research.contrary.com/company/mercor (accessed 2026-06-07)
- status: active [confirmed], source: https://techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/ (accessed 2026-06-07)
- hq_location: San Francisco, CA, USA (181 Fremont) [confirmed], source: https://en.wikipedia.org/wiki/Mercor (accessed 2026-06-07); https://www.linkedin.com/company/mercor-ai (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: yes [reported], source: https://en.wikipedia.org/wiki/Mercor (accessed 2026-06-07; global contractor network across 6 continents)
- current_headcount: LinkedIn public band 51-200 (full-time employees); separately operates a network of ~30,000+ contractors. Wikipedia cites ~300 'employees' (2025) but this likely blends staff and contractors; aggregator figures of 3,000+ clearly count the contractor network [reported], source: https://www.linkedin.com/company/mercor-ai (accessed 2026-06-07); https://en.wikipedia.org/wiki/Mercor (accessed 2026-06-07)
- headcount_band: 51-200 [reported], source: https://www.linkedin.com/company/mercor-ai (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown]
- has_researchers: yes [confirmed], source: https://www.mercor.com/research/ (accessed 2026-06-07)
- researcher_count: unknown [unknown]
- researcher_backgrounds: Founders Brendan Foody, Adarsh Hiremath, Surya Midha are Thiel Fellows and college dropouts (not research-lab veterans); Sundeep Jain (President, hired May 2025) ex-Uber CPO/SVP Eng and ex-Google VP Product [reported], source: https://en.wikipedia.org/wiki/Mercor (accessed 2026-06-07); https://research.contrary.com/company/mercor (accessed 2026-06-07)
- published_papers_or_benchmarks: APEX (AI Productivity Index); APEX-Agents; APEX-SWE; ACE (AI Consumer Index) [confirmed], source: https://www.mercor.com/research/ (accessed 2026-06-07)
- total_raised: ~$492M across 4 rounds (Seed ~$3M+, Series A $30M, Series B $100M, Series C $350M) [reported], source: https://tracxn.com/d/companies/mercor (accessed 2026-06-07); corroborated by https://techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/ (accessed 2026-06-07)
- last_round: Series C, $350M, October 2025 [confirmed], source: https://techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/ (accessed 2026-06-07)
- notable_investors: Felicis Ventures (led Series C and Series B); Benchmark; General Catalyst; Robinhood Ventures [confirmed], source: https://techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/ (accessed 2026-06-07)
- valuation: $10B (Series C, Oct 2025) [confirmed], source: https://techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/ (accessed 2026-06-07); https://www.cnbc.com/2025/10/27/ai-hiring-startup-mercor-funding.html (accessed 2026-06-07)
- revenue_signals: On track to ~$500M ARR (reported Oct 2025); pays contractors >$1.5M/day (implying ~$840M run-rate gross) [reported], source: https://techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/ (accessed 2026-06-07)
- soc2: unknown [unknown], source: https://trust.mercor.com/ (accessed 2026-06-07; trust center exists but certification details not extractable from public page; note: press reports Mercor's compliance vendor Delve was accused of issuing fraudulent SOC 2 reports, casting doubt on any prior claimed certification)
- other_certifications: unknown [unknown]
- security_page: https://trust.mercor.com/ [confirmed], source: https://trust.mercor.com/ (accessed 2026-06-07)
- what_they_sell: mixed [confirmed], source: https://www.mercor.com/research/ (accessed 2026-06-07)
- open_source: no [estimated]
- license: unknown [unknown]
- deployment_model: managed-hosted (managed service / marketplace; RL environments delivered as a service to labs) [estimated], source: https://www.mercor.com/research/ (accessed 2026-06-07)
- maturity: GA [reported], source: https://techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/ (accessed 2026-06-07)
- notable_customers: OpenAI (verified, frontier-lab tie); Anthropic (verified, frontier-lab tie); Meta (verified, frontier-lab tie); Google DeepMind (verified, frontier-lab tie) [reported], source: https://techcrunch.com/2025/10/29/how-ai-labs-use-mercor-to-get-the-data-companies-wont-share/ (accessed 2026-06-07; names OpenAI, Anthropic, Meta); https://theaiinsider.tech/2025/10/29/mercor-raises-350m-to-scale-expert-driven-ai-training-reaching-10b-valuation/ (accessed 2026-06-07; names OpenAI, Google DeepMind, Meta). Third-party press, not vendor logo wall.
- sources:
  - https://www.mercor.com/ (accessed 2026-06-07)
  - https://www.mercor.com/research/ (accessed 2026-06-07)
  - https://techcrunch.com/2025/10/27/mercor-quintuples-valuation-to-10b-with-350m-series-c/ (accessed 2026-06-07)
  - https://en.wikipedia.org/wiki/Mercor (accessed 2026-06-07)
  - https://www.orrick.com/en/News/2026/02/Mercor-Acquires-Sepal-AI (accessed 2026-06-07)
  - https://theaiinsider.tech/2025/10/29/mercor-raises-350m-to-scale-expert-driven-ai-training-reaching-10b-valuation/ (accessed 2026-06-07)
  - https://tracxn.com/d/companies/mercor/__764DkS7wJgmA1B8PuOw3_4HUbgJcaKjh8xY9UxvBIpY/funding-and-investors (accessed 2026-06-07)
  - https://trust.mercor.com/ (accessed 2026-06-07)
  - https://techcrunch.com/2026/03/31/mercor-says-it-was-hit-by-cyberattack-tied-to-compromise-of-open-source-litellm-project/ (accessed 2026-06-07)
  - https://techcrunch.com/2026/04/09/after-data-breach-10b-valued-startup-mercor-is-having-a-month/ (accessed 2026-06-07)
  - https://newsletter.semianalysis.com/p/rl-environments-and-rl-for-science (accessed 2026-06-07)

## Surge AI (not ranked, incumbent / infrastructure / open-source)
- slug: surge-ai
- segment: Incumbents also building RL environments
- website: https://surgehq.ai/
- focus_areas: Enterprise Workflows, Long-Horizon
- positioning: Surge AI is a bootstrapped, high-revenue human-data and RLHF labeling leader serving frontier AI labs, which has expanded into agentic RL environments via its EnterpriseBench suite (notably the CoreCraft enterprise customer-support simulation) and accompanying published benchmarks. As of June 2026 a reported ~$1B first external raise at a ~$25B valuation was in talks but not confirmed closed.
- best_fit: Buyers needing expert human-feedback/RLHF data plus realistic enterprise-workflow RL environments and rubric-based agent evaluation from an established, frontier-lab-trusted vendor.
- overall_confidence: medium
- founded_year: 2020 [reported], source: https://en.wikipedia.org/wiki/Surge_AI accessed 2026-06-07 (founded 2020 by Edwin Chen); corroborated by CB Insights/Craft. Note: Sacra describes a '2021 launch'; getlatka lists '2018' (outlier). Single primary source, so reported.
- status: active [confirmed], source: https://surgehq.ai/ accessed 2026-06-07; https://en.wikipedia.org/wiki/Surge_AI accessed 2026-06-07
- hq_location: San Francisco, California, USA [confirmed], source: https://en.wikipedia.org/wiki/Surge_AI accessed 2026-06-07; Craft.co lists 2193 Fillmore St, San Francisco accessed 2026-06-07
- other_locations: unknown [unknown], source: No additional offices disclosed; careers roles listed as Remote. https://surgehq.ai/careers accessed 2026-06-07
- distributed_remote: yes [reported], source: https://surgehq.ai/careers accessed 2026-06-07 (open roles listed Remote); ~1M distributed annotator/contractor network per https://en.wikipedia.org/wiki/Surge_AI accessed 2026-06-07
- current_headcount: ~110-121 full-time employees (2025); ~1M annotators/contractors [reported], source: https://en.wikipedia.org/wiki/Surge_AI accessed 2026-06-07 (110 employees, 2025); getlatka/Inc. cite ~121 FTE; ~1M annotators. Pitchbook ~250 is an outlier and not relied upon.
- headcount_band: 51-200 [confirmed], source: https://www.linkedin.com/company/surge-ai accessed 2026-06-07 (public band 51-200); corroborated by Craft.co accessed 2026-06-07. Refers to full-time staff, not the ~1M contractor network.
- headcount_growth: unknown [unknown]
- open_roles_count: 41 [reported], source: https://surgehq.ai/careers accessed 2026-06-07 (draft figure; not independently re-counted)
- has_researchers: yes [confirmed], source: https://surgehq.ai/research accessed 2026-06-07 (published benchmarks/RL environments; arXiv:2602.16179 EnterpriseBench CoreCraft); https://surgehq.ai/careers lists Research Scientist roles, accessed 2026-06-07
- researcher_count: unknown [unknown], source: Research roles/fellowship advertised but team count not disclosed. accessed 2026-06-07
- researcher_backgrounds: Founder/CEO Edwin Chen: ex-Google, ex-Facebook, ex-Twitter ML teams; MIT background (reportedly did not complete degree) [reported], source: https://en.wikipedia.org/wiki/Surge_AI accessed 2026-06-07; getlatka describes him as 'MIT Dropout'
- published_papers_or_benchmarks: EnterpriseBench CoreCraft: Training Generalizable Agents on High-Fidelity RL Environments - arXiv:2602.16179 (https://arxiv.org/abs/2602.16179); CoreCraft enterprise customer-support simulation (2,500+ entities, 14 entity types, 23 tools) - https://surgehq.ai/blog/enterprisebench-corecraft; AdvancedIF (1,600+ prompts, expert rubrics) - https://surgehq.ai/research; Complex-IF / Riemann-Bench / SciReview / GDP.PDF / Multimodal RewardBench 2 - https://surgehq.ai/research [confirmed], source: https://surgehq.ai/research accessed 2026-06-07; arXiv:2602.16179 accessed 2026-06-07
- total_raised: Bootstrapped / no confirmed closed external round as of June 2026; first external raise (~$1B primary+secondary) reportedly initiated July 2025 but not confirmed closed [reported], source: https://en.wikipedia.org/wiki/Surge_AI accessed 2026-06-07; https://sacra.com/c/surge-ai/ accessed 2026-06-07 ('first-ever capital raise after operating profitably since launch'); https://www.bloomberg.com/news/articles/2025-07-30/scale-rival-surge-ai-in-talks-for-funding-at-25-billion-value accessed 2026-06-07
- last_round: In talks (July 2025) for ~$1B primary+secondary; NOT confirmed closed as of June 2026 [reported], source: https://www.bloomberg.com/news/articles/2025-07-30/scale-rival-surge-ai-in-talks-for-funding-at-25-billion-value accessed 2026-06-07 (in talks; J.P. Morgan facilitating secondary). A LinkedIn post claiming a closed $30B round is not a credible source and is not relied upon.
- notable_investors: unknown [unknown], source: No confirmed investors; round not confirmed closed. Bloomberg named only POTENTIAL investors (Andreessen Horowitz, Warburg Pincus, TPG) with J.P. Morgan facilitating secondary. https://www.bloomberg.com/news/articles/2025-07-30/scale-rival-surge-ai-in-talks-for-funding-at-25-billion-value accessed 2026-06-07
- valuation: ~$25B (reported July 2025 fundraise talks; 'at least $25B' per Bloomberg, '>$15B' per Reuters); unconfirmed/not closed [reported], source: https://www.bloomberg.com/news/articles/2025-07-30/scale-rival-surge-ai-in-talks-for-funding-at-25-billion-value accessed 2026-06-07. getlatka's $20B and a LinkedIn $30B claim are inconsistent/weak and not relied upon.
- revenue_signals: $1.2B revenue (2024); ~$1.4B ARR claimed (Aug 2025, weak source) [reported], source: $1.2B 2024 corroborated by https://en.wikipedia.org/wiki/Surge_AI and https://sacra.com/c/surge-ai/ accessed 2026-06-07. The ~$1.4B ARR figure is from getlatka.com (low-reliability aggregator) only. Note: Meta reportedly ~$150M/yr, Google ~$100M/yr (Sacra).
- soc2: unknown [unknown], source: No public trust/security page or SOC 2 statement found. accessed 2026-06-07
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: No dedicated security/trust page found. accessed 2026-06-07
- what_they_sell: mixed [confirmed], source: https://surgehq.ai/ and https://surgehq.ai/research accessed 2026-06-07 (human data/RLHF labeling platform plus agentic RL environments). Core business is human data; environments are an adjacent/secondary line.
- open_source: no [reported], source: https://surgehq.ai/research accessed 2026-06-07 (benchmarks published as arXiv papers; EnterpriseBench/CoreCraft described as proprietary; no OSS license/repo disclosed)
- license: unknown [unknown]
- deployment_model: managed-hosted [estimated], source: https://surgehq.ai/ accessed 2026-06-07 (managed human-data platform/service; no self-hosted/on-prem offering disclosed)
- maturity: GA [estimated], source: https://surgehq.ai/ accessed 2026-06-07; revenue-generating platform ($1.2B 2024) serving frontier labs per https://sacra.com/c/surge-ai/ accessed 2026-06-07
- notable_customers: Anthropic (verified, frontier-lab tie); Google (verified, frontier-lab tie); Meta (verified, frontier-lab tie); Microsoft (verified, frontier-lab tie); OpenAI (former; relationship reportedly ended) (verified, frontier-lab tie) [reported], source: Anthropic: Jared Kaplan endorsement on Surge's own blog https://surgehq.ai/blog/anthropic-surge-ai-rlhf-platform-train-llm-assistant-human-feedback accessed 2026-06-07 PLUS third-party Sacra. Google/Meta/Microsoft/OpenAI named by third-party https://sacra.com/c/surge-ai/ ('~12 frontier labs, most notably OpenAI, Google, Anthropic, Microsoft, Meta') and Inc. magazine, accessed 2026-06-07. OpenAI: a Forbes report (Sept 2025) cited an OpenAI spokesperson saying they NO LONGER work with Surge AI.
- sources:
  - https://surgehq.ai/ (accessed 2026-06-07)
  - https://surgehq.ai/research (accessed 2026-06-07)
  - https://surgehq.ai/careers (accessed 2026-06-07)
  - https://surgehq.ai/blog/anthropic-surge-ai-rlhf-platform-train-llm-assistant-human-feedback (accessed 2026-06-07)
  - https://en.wikipedia.org/wiki/Surge_AI (accessed 2026-06-07)
  - https://sacra.com/c/surge-ai/ (accessed 2026-06-07)
  - https://www.bloomberg.com/news/articles/2025-07-30/scale-rival-surge-ai-in-talks-for-funding-at-25-billion-value (accessed 2026-06-07)
  - https://getlatka.com/companies/surgehq.ai (accessed 2026-06-07)
  - https://www.linkedin.com/company/surge-ai (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/472331-53 (accessed 2026-06-07)

## Prime Intellect (not ranked, incumbent / infrastructure / open-source)
- slug: prime-intellect
- segment: Open-source & open environments
- website: https://www.primeintellect.ai/
- focus_areas: Coding, Enterprise Workflows, Long-Horizon, Math
- positioning: Prime Intellect operates an open-source RL stack - the Environments Hub (2,500+ community RL environments), the Verifiers library and prime-rl training framework, plus hosted RL post-training (Lab), evals, inference and on-demand GPU compute. It positions itself as the open alternative to closed big-lab RL tooling and also trains open models (INTELLECT series).
- best_fit: Teams wanting open, community-shared RL environments plus managed RL post-training/compute to build or fine-tune agentic models without locked-down proprietary tooling.
- overall_confidence: medium
- founded_year: 2023 [reported], source: https://tracxn.com/d/companies/prime-intellect/__c00KIKAVH9b1POsp5fnIynw_8joG2ie8qsqmCTAB6Bc (accessed 2026-06-07) - multiple aggregators state founded 2023 by Vincent Weisser & Johannes Hagemann; no primary registry confirmation
- status: active [confirmed], source: https://www.primeintellect.ai/ (accessed 2026-06-07); active GitHub releases and blog posts through 2026
- hq_location: San Francisco, USA [confirmed], source: https://www.linkedin.com/company/primeintellect-ai (accessed 2026-06-07) - public snippet lists San Francisco, US
- other_locations: unknown [unknown]
- distributed_remote: yes [reported], source: https://wellfound.com/company/prime-intellect/jobs (accessed 2026-06-07) - several roles list remote/flexible location
- current_headcount: 11-50 (LinkedIn public snippet, as of 2026-06-07); Sacra reported 23 FTE (date unclear, likely 2025) [reported], source: https://www.linkedin.com/company/primeintellect-ai (accessed 2026-06-07); https://sacra.com/c/prime-intellect/ (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/primeintellect-ai (accessed 2026-06-07) - public snippet '11-50 employees'; consistent with Sacra 23 FTE
- headcount_growth: 229% YoY (per Sacra; period unspecified, likely 2024-2025, stale) [reported], source: https://sacra.com/c/prime-intellect/ (accessed 2026-06-07) - single-source aggregator, period not stated
- open_roles_count: ~28-29 open roles [reported], source: https://www.fastaijobs.com/companies/prime-intellect (accessed 2026-06-07); https://wellfound.com/company/prime-intellect/jobs (accessed 2026-06-07)
- has_researchers: yes [confirmed], source: https://arxiv.org/abs/2512.16144 (accessed 2026-06-07) - INTELLECT-3 Technical Report authored by 'Prime Intellect Team'; hiring Research Engineers
- researcher_count: unknown [unknown]
- researcher_backgrounds: Johannes Hagemann (co-founder/CTO) - ex-Aleph Alpha (distributed training); Will Brown - created Verifiers RL environments library; research lead (not a founder); Vincent Weisser (co-founder/CEO) - background in DeSci/Web3 (e.g. VitaDAO) [reported], source: https://nextomoro.com/johannes-hagemann/ (accessed 2026-06-07); https://github.com/PrimeIntellect-ai/verifiers (accessed 2026-06-07) - 'Originally created by Will Brown (@willccbb)'; https://www.vincentweisser.com/ (accessed 2026-06-07)
- published_papers_or_benchmarks: INTELLECT-2: The First Globally Distributed RL Training of a 32B Parameter Model (https://www.primeintellect.ai/blog/intellect-2); INTELLECT-3: Technical Report - 106B MoE (12B active) trained with large-scale RL (https://arxiv.org/abs/2512.16144) [confirmed], source: https://www.primeintellect.ai/blog/intellect-2 (accessed 2026-06-07); https://arxiv.org/abs/2512.16144 (accessed 2026-06-07) - authored by 'Prime Intellect Team'
- total_raised: ~$70.4M (reported by aggregator); confirmed components: $5.5M seed (Apr 2024) + $15M (Feb 2025); a ~$49.9M Series B (Dec 2025) is reported by Tracxn only [reported], source: https://tracxn.com/d/companies/prime-intellect/__c00KIKAVH9b1POsp5fnIynw_8joG2ie8qsqmCTAB6Bc/funding-and-investors (accessed 2026-06-07) - single aggregator for the $70.4M total / Series B; seed and $15M rounds independently confirmed via PRNewswire/Fortune and official blog
- last_round: Series B, ~$49.9M, December 2025 (reported by Tracxn aggregator only; no primary announcement located) [reported], source: https://tracxn.com/d/companies/prime-intellect/__c00KIKAVH9b1POsp5fnIynw_8joG2ie8qsqmCTAB6Bc/funding-and-investors (accessed 2026-06-07)
- notable_investors: Founders Fund (led $15M round); Menlo Ventures; Distributed Global (co-led seed); CoinFund (co-led seed); Andrej Karpathy (angel); Clem Delangue / Hugging Face (angel); Tri Dao (angel); Emad Mostaque (angel); Dylan Patel (angel) [reported], source: https://www.primeintellect.ai/blog/fundraise (accessed 2026-06-07) - official $15M announcement naming Founders Fund, Menlo, Karpathy, Delangue, Tri Dao, Mostaque, Dylan Patel; https://www.prnewswire.com/news-releases/prime-intellect-secures-5-5m-in-seed-funding-co-led-by-distributed-global-and-coinfund-302124585.html (accessed 2026-06-07) - seed co-leads
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: mixed [confirmed], source: https://www.primeintellect.ai/ (accessed 2026-06-07) - GPU compute, managed RL post-training (Lab), hosted inference, Environments Hub, and open-source environments/frameworks (verifiers, prime-rl)
- open_source: yes [confirmed], source: https://github.com/PrimeIntellect-ai/verifiers (accessed 2026-06-07) - MIT-licensed library; https://github.com/PrimeIntellect-ai/prime-rl (accessed 2026-06-07)
- license: MIT (Verifiers library); other repos vary [confirmed], source: https://github.com/PrimeIntellect-ai/verifiers (accessed 2026-06-07) - MIT license confirmed; created by Will Brown (@willccbb), maintained by PrimeIntellect-ai
- deployment_model: managed-hosted + API (hosted training/inference, on-demand GPU); open-source frameworks self-hostable [confirmed], source: https://www.primeintellect.ai/ (accessed 2026-06-07); https://github.com/PrimeIntellect-ai/verifiers (accessed 2026-06-07)
- maturity: GA (platform live; Environments Hub and Lab publicly available) [reported], source: https://www.primeintellect.ai/blog/environments (accessed 2026-06-07); https://docs.primeintellect.ai/ (accessed 2026-06-07)
- notable_customers: NVIDIA (integration/collaboration - Prime Intellect integrates NVIDIA NeMo Gym training environments; per NVIDIA newsroom) (verified, frontier-lab tie); Zapier (case study - AutomationBench agent improvement loop) (self-claimed); Ramp (case study - FastAsk subagent trained via Lab) (self-claimed); Arcee AI (self-claimed); Character AI (self-claimed); Browserbase (self-claimed); Groq (self-claimed) [reported], source: https://nvidianews.nvidia.com/news/nvidia-debuts-nemotron-3-family-of-open-models (accessed 2026-06-07) - NVIDIA newsroom confirms Prime Intellect integrating NeMo Gym (note: this is Prime Intellect adopting NVIDIA tooling, not NVIDIA buying from Prime Intellect); https://www.primeintellect.ai/case-study/zapier and /case-study/ramp and homepage logos (accessed 2026-06-07) - vendor's own site, self-claimed
- sources:
  - https://www.primeintellect.ai/ (accessed 2026-06-07)
  - https://www.primeintellect.ai/blog/environments (accessed 2026-06-07)
  - https://www.primeintellect.ai/blog/fundraise (accessed 2026-06-07)
  - https://www.prnewswire.com/news-releases/prime-intellect-secures-5-5m-in-seed-funding-co-led-by-distributed-global-and-coinfund-302124585.html (accessed 2026-06-07)
  - https://tracxn.com/d/companies/prime-intellect/__c00KIKAVH9b1POsp5fnIynw_8joG2ie8qsqmCTAB6Bc/funding-and-investors (accessed 2026-06-07)
  - https://sacra.com/c/prime-intellect/ (accessed 2026-06-07)
  - https://www.linkedin.com/company/primeintellect-ai (accessed 2026-06-07)
  - https://github.com/PrimeIntellect-ai/verifiers (accessed 2026-06-07)
  - https://github.com/PrimeIntellect-ai/prime-rl (accessed 2026-06-07)
  - https://www.primeintellect.ai/case-study/zapier (accessed 2026-06-07)
  - https://www.primeintellect.ai/case-study/ramp (accessed 2026-06-07)
  - https://www.primeintellect.ai/blog/intellect-3 (accessed 2026-06-07)
  - https://arxiv.org/pdf/2512.16144 (accessed 2026-06-07)
  - https://arxiv.org/pdf/2601.16443 (accessed 2026-06-07)
  - https://nextomoro.com/johannes-hagemann/ (accessed 2026-06-07)
  - https://www.vincentweisser.com/ (accessed 2026-06-07)
  - https://www.fastaijobs.com/companies/prime-intellect (accessed 2026-06-07)
  - https://wellfound.com/company/prime-intellect/jobs (accessed 2026-06-07)
  - https://www.sequoiacap.com/podcast/building-the-github-for-rl-environments-prime-intellects-will-brown-johannes-hagemann/ (accessed 2026-06-07)

## Daytona (not ranked, incumbent / infrastructure / open-source)
- slug: daytona
- segment: Adjacent: execution infrastructure
- website: https://www.daytona.io/
- focus_areas: Coding, Computer Use
- positioning: Daytona provides secure, elastic, programmatic sandboxes ('computers') that AI agents and developers can spin up in under ~90ms to run untrusted AI-generated code in isolated, stateful runtimes. It offers a managed-hosted service plus an open-source self-hostable stack, and is positioned as agent-native execution/runtime infrastructure for code execution, computer use, and RL/eval workloads.
- best_fit: Buyers needing fast, isolated, programmatic sandboxes to safely execute AI-generated code or run agent tool/computer-use loops at scale.
- overall_confidence: high
- founded_year: 2023 [reported], source: https://www.linkedin.com/company/daytonaio (accessed 2026-06-07); pre-seed Nov 2023 per https://www.daytona.io/dotfiles/daytona-secures-5m-to-simplify-development-environments (accessed 2026-06-07)
- status: active [confirmed], source: https://www.daytona.io/ (accessed 2026-06-07); raised Series A Feb 2026
- hq_location: New York, NY, United States [reported], source: https://tracxn.com/d/companies/daytona (accessed 2026-06-07); https://www.daytona.io/dotfiles/daytona-lights-up-times-square (accessed 2026-06-07). Note: a LinkedIn public snippet also surfaced San Francisco, CA as an associated location
- other_locations: San Francisco, CA (work location for open roles / community events); Croatia (work location for open roles) [reported], source: https://www.daytona.io/careers (accessed 2026-06-07), listed as work locations for open roles; founders are Croatia-connected (ex-Codeanywhere)
- distributed_remote: yes [reported], source: https://www.daytona.io/careers (accessed 2026-06-07), roles open across NY, SF, and Croatia
- current_headcount: ~20 (Feb 2026, company-stated at Series A); third-party trackers list ~63 associated profiles and an 11-50 band as of 2026-06-07 [reported], source: https://www.prnewswire.com/news-releases/daytona-raises-24m-series-a-to-give-every-agent-a-computer-302680740.html and https://tracxn.com/d/companies/daytona and https://www.linkedin.com/company/daytonaio (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/daytonaio (accessed 2026-06-07), LinkedIn size band; company stated ~20 at Series A
- headcount_growth: unknown [unknown]
- open_roles_count: 10 [reported], source: https://www.daytona.io/careers (accessed 2026-06-07)
- has_researchers: unknown [unknown]
- researcher_count: unknown [unknown]
- researcher_backgrounds: Founders Ivan Burazin (CEO), Vedran Jukic (CTO), Goran Draganic (Chief Architect) previously co-founded Codeanywhere, a cloud IDE/dev-environment company; Burazin was also Chief Developer Experience Officer at Infobip [reported], source: https://www.daytona.io/dotfiles/daytona-secures-5m-to-simplify-development-environments (accessed 2026-06-07)
- published_papers_or_benchmarks: unknown [unknown]
- total_raised: ~$31M total disclosed ($2M pre-seed Nov 2023 + $5M seed Jun 2024 + $24M Series A Feb 2026) [reported], source: https://www.daytona.io/dotfiles/daytona-secures-5m-to-simplify-development-environments; https://www.prnewswire.com/news-releases/daytona-raises-24m-series-a-to-give-every-agent-a-computer-302680740.html; https://tracxn.com/d/companies/daytona (accessed 2026-06-07)
- last_round: Series A, $24M, February 2026 [confirmed], source: https://www.prnewswire.com/news-releases/daytona-raises-24m-series-a-to-give-every-agent-a-computer-302680740.html (accessed 2026-06-07)
- notable_investors: FirstMark Capital (Series A lead; Matt Turck joined board); Pace Capital; Upfront Ventures (seed lead, Series A participant); E2VC; Darkmode; Datadog (strategic); Figma Ventures (strategic); 500 Global (seed; not named in Series A release) [reported], source: https://www.prnewswire.com/news-releases/daytona-raises-24m-series-a-to-give-every-agent-a-computer-302680740.html (FirstMark, Pace, Upfront, E2VC, Darkmode, Datadog, Figma Ventures); https://www.daytona.io/dotfiles/daytona-secures-5m-to-simplify-development-environments (Upfront, 500 Global) (accessed 2026-06-07). Note: angel investors (Yurtseven, Browne, Reyes, Shamgunov) listed in the draft were NOT found in the primary Series A release and are removed pending a primary source
- valuation: unknown [unknown]
- revenue_signals: Company-claimed: ~$1M forward revenue run rate within three months, doubled six weeks later (as of Series A, Feb 2026) [reported], source: https://www.prnewswire.com/news-releases/daytona-raises-24m-series-a-to-give-every-agent-a-computer-302680740.html (accessed 2026-06-07), vendor-stated, unaudited
- soc2: Type I [reported], source: https://trust.daytona.io/ (accessed 2026-06-07), SOC 2 Type 1 report listed in Trust Center; not independently verified against an audit registry
- other_certifications: HIPAA (report listed in Trust Center); ISO/IEC 27001 (listed in Trust Center; certified vs in-progress not stated); GDPR (listed in Trust Center) [reported], source: https://trust.daytona.io/ (accessed 2026-06-07)
- security_page: https://trust.daytona.io/ [confirmed], source: https://trust.daytona.io/ (accessed 2026-06-07)
- what_they_sell: infra [confirmed], source: https://www.daytona.io/ (accessed 2026-06-07)
- open_source: yes [confirmed], source: https://github.com/daytonaio/daytona (accessed 2026-06-07)
- license: AGPL-3.0 [confirmed], source: https://github.com/daytonaio/daytona (accessed 2026-06-07)
- deployment_model: managed-hosted and self-hosted (open source) [confirmed], source: https://www.daytona.io/ (accessed 2026-06-07); https://github.com/daytonaio/daytona (accessed 2026-06-07)
- maturity: GA [reported], source: https://www.prnewswire.com/news-releases/daytona-raises-24m-series-a-to-give-every-agent-a-computer-302680740.html (accessed 2026-06-07), commercial product with paying customers and revenue run rate
- notable_customers: Anthropic, Claude Managed Agents self-hosted sandbox launch partner (platform integration, one of four: Cloudflare, Daytona, Modal, Vercel), NOT a disclosed Daytona customer (verified, frontier-lab tie); Clay (Sculptor GTM agent runs in production on Claude Managed Agents + Daytona) (verified); LangChain (self-claimed); Turing (self-claimed); Writer (self-claimed); SambaNova (self-claimed) [reported], source: LangChain/Turing/Writer/SambaNova self-claimed via https://www.prnewswire.com/news-releases/daytona-raises-24m-series-a-to-give-every-agent-a-computer-302680740.html; Anthropic partnership and Clay production usage verified via https://thenewstack.io/anthropic-mcp-tunnels-sandboxes/ and https://claude.com/customers/clay and https://www.daytona.io/docs/en/guides/claude/claude-managed-agents/ (accessed 2026-06-07)
- sources:
  - https://www.daytona.io/ (accessed 2026-06-07)
  - https://github.com/daytonaio/daytona (accessed 2026-06-07)
  - https://www.prnewswire.com/news-releases/daytona-raises-24m-series-a-to-give-every-agent-a-computer-302680740.html (accessed 2026-06-07)
  - https://www.daytona.io/dotfiles/daytona-raises-24m-series-a-to-give-every-agent-a-computer (accessed 2026-06-07)
  - https://www.daytona.io/dotfiles/daytona-secures-5m-to-simplify-development-environments (accessed 2026-06-07)
  - https://www.linkedin.com/company/daytonaio (accessed 2026-06-07)
  - https://trust.daytona.io/ (accessed 2026-06-07)
  - https://www.daytona.io/careers (accessed 2026-06-07)
  - https://www.anthropic.com/engineering/managed-agents (accessed 2026-06-07)
  - https://www.daytona.io/docs/en/guides/claude/claude-managed-agents/ (accessed 2026-06-07)
  - https://tracxn.com/d/companies/daytona/__TzaXWUoUzJqHEQmWu6SWgVcuHYFltYtBs_uhDgw84Ss (accessed 2026-06-07)

## E2B (not ranked, incumbent / infrastructure / open-source)
- slug: e2b
- segment: Adjacent: execution infrastructure
- website: https://e2b.dev/
- focus_areas: Coding, Computer Use
- positioning: E2B provides open-source, secure cloud sandboxes (built on Firecracker microVMs) for running AI-generated code and AI agents, offered as a hosted API with BYOC/on-prem/self-hosted options. It positions as execution infrastructure for enterprise AI agents and self-claims broad Fortune 100 adoption.
- best_fit: Buyers needing secure, isolated runtime infrastructure to execute LLM-generated code or run agents at scale, including as a sandbox layer for RL/agent training.
- overall_confidence: medium
- founded_year: 2023 [reported], source: https://tracxn.com/d/companies/e2b (accessed 2026-06-07); https://www.crunchbase.com/organization/e2b-1c91 (accessed 2026-06-07)
- status: active [confirmed], source: https://e2b.dev/ (accessed 2026-06-07); https://e2b.dev/blog/series-a (accessed 2026-06-07)
- hq_location: San Francisco, USA [confirmed], source: https://www.linkedin.com/company/e2b-dev (accessed 2026-06-07); https://e2b.dev/blog/series-a (accessed 2026-06-07)
- other_locations: Prague, Czech Republic [reported], source: https://www.linkedin.com/company/e2b-dev (accessed 2026-06-07)
- distributed_remote: yes [estimated], source: Team distributed across US (San Francisco) and Czech Republic (Prague) per LinkedIn; https://www.linkedin.com/company/e2b-dev (accessed 2026-06-07)
- current_headcount: 11-50 (LinkedIn company size band; ~37 employees listed on LinkedIn as of 2026-06-07) [reported], source: https://www.linkedin.com/company/e2b-dev (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://www.linkedin.com/company/e2b-dev (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: ~12-13 open roles [reported], source: https://www.glassdoor.com/Jobs/E2B-Jobs-E10750951.htm and https://e2b.dev/careers (accessed 2026-06-07)
- has_researchers: no [estimated], source: Team and open roles appear engineering/infra/DevRel/GTM focused, not research scientists; https://e2b.dev/careers (accessed 2026-06-07)
- researcher_count: unknown [unknown]
- researcher_backgrounds: unknown [unknown]
- published_papers_or_benchmarks: unknown [unknown]
- total_raised: ~$32M (official Series A blog states $32M total) [reported], source: https://e2b.dev/blog/series-a (accessed 2026-06-07) - $11.5M seed + $21M Series A = $32M; some third-party aggregators (Tracxn) report ~$35M+
- last_round: Series A, $21M, July 2025 (announced 2025-07-28) [confirmed], source: https://e2b.dev/blog/series-a (accessed 2026-06-07); https://www.prnewswire.com/news-releases/e2b-raises-a-21m-series-a-to-offer-cloud-for-ai-agents-to-fortune-100-302514540.html (accessed 2026-06-07)
- notable_investors: Insight Partners (Series A lead); Decibel (seed lead); Sunflower Capital; Kaya / Kaya VC; Scott Johnston (former Docker CEO, angel) [confirmed], source: https://e2b.dev/blog/series-a (accessed 2026-06-07); https://www.insightpartners.com/ideas/e2b-raises-a-21m-series-a-to-offer-cloud-for-ai-agents-to-fortune-100/ (accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown (vendor self-claims conflict: a careers snippet referenced '8-figure revenue' / '$37M since founding' while a LinkedIn snippet states '7-figure revenue'; none independently verified) [unknown], source: https://e2b.dev/careers and https://www.linkedin.com/company/e2b-dev (accessed 2026-06-07) - conflicting self-claimed figures, no credible third-party confirmation
- soc2: claimed-unverified (vendor trust center states SOC 2 Type II) [reported], source: https://trust.e2b.dev/ (accessed 2026-06-07) - trust center is vendor-hosted and JS-rendered; SOC 2 Type II claim could not be independently confirmed via an audit registry or third party
- other_certifications: ISO 27001 (claimed-unverified); HIPAA (claimed-unverified); GDPR (claimed-unverified) [reported], source: https://trust.e2b.dev/ (accessed 2026-06-07) - claimed on vendor trust center only; not independently verified
- security_page: https://trust.e2b.dev/ [confirmed], source: https://trust.e2b.dev/ (accessed 2026-06-07)
- what_they_sell: infra [confirmed], source: https://e2b.dev/ (accessed 2026-06-07) - secure cloud sandboxes (Firecracker microVMs) for running AI-generated code and AI agents; RL training is one stated use case
- open_source: yes [confirmed], source: https://github.com/e2b-dev/E2B (accessed 2026-06-07)
- license: Apache-2.0 [confirmed], source: https://github.com/e2b-dev/E2B (accessed 2026-06-07)
- deployment_model: managed-hosted (cloud API), with BYOC, on-prem, and self-hosted options in customer AWS/GCP/Azure accounts [confirmed], source: https://e2b.dev/ (accessed 2026-06-07) - lists BYOC, on-premises, and self-hosted deployment
- maturity: GA [confirmed], source: https://e2b.dev/ (accessed 2026-06-07) - usage-based pricing, published SDKs, enterprise customers
- notable_customers: Perplexity (self-claimed); Hugging Face (self-claimed); Groq (self-claimed); Manus (self-claimed); Lindy (self-claimed); Genspark (self-claimed); Gumloop (self-claimed); Athena (self-claimed) [reported], source: https://e2b.dev/ and https://e2b.dev/blog/series-a (accessed 2026-06-07) - all customer names from vendor's own homepage/Series A materials (self-claimed). Vendor also claims '94% of Fortune 100' on homepage (was '88%' in the July 2025 Series A post) - a self-claimed, unverifiable aggregate
- sources:
  - https://e2b.dev/ (accessed 2026-06-07)
  - https://e2b.dev/enterprise (accessed 2026-06-07)
  - https://e2b.dev/blog/series-a (accessed 2026-06-07)
  - https://e2b.dev/careers (accessed 2026-06-07)
  - https://github.com/e2b-dev/E2B (accessed 2026-06-07)
  - https://trust.e2b.dev/ (accessed 2026-06-07)
  - https://trust.e2b.dev/controls (accessed 2026-06-07)
  - https://www.linkedin.com/company/e2b-dev (accessed 2026-06-07)
  - https://www.insightpartners.com/ideas/e2b-raises-a-21m-series-a-to-offer-cloud-for-ai-agents-to-fortune-100/ (accessed 2026-06-07)
  - https://www.prnewswire.com/news-releases/e2b-raises-a-21m-series-a-to-offer-cloud-for-ai-agents-to-fortune-100-302514540.html (accessed 2026-06-07)
  - https://venturebeat.com/ai/how-e2b-became-essential-to-88-of-fortune-100-companies-and-raised-21-million (accessed 2026-06-07)
  - https://tracxn.com/d/companies/e2b/__U7C82j6Wk3VH-rgW0n4LFnUqqq-LuBw6rnIcnLGz2yU/funding-and-investors (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/e2b-1c91 (accessed 2026-06-07)
  - https://www.glassdoor.com/Jobs/E2B-Jobs-E10750951.htm (accessed 2026-06-07)

## Runloop (not ranked, incumbent / infrastructure / open-source)
- slug: runloop
- segment: Adjacent: execution infrastructure
- website: https://runloop.ai/
- focus_areas: Coding
- positioning: Runloop sells cloud-hosted, isolated micro-VM 'devboxes' plus blueprints, snapshots and benchmark/eval tooling that give AI coding agents a secure execution environment for development, evaluation, and reinforcement/supervised fine-tuning (RFT/SFT) loops. It is execution infrastructure for agent builders and model labs rather than an RL-data/environments vendor itself.
- best_fit: Teams building or training coding agents that need scalable, sandboxed execution environments to run agents, evals (SWE-Bench, etc.), and RFT/SFT loops.
- overall_confidence: medium
- founded_year: 2024 [reported], source: https://www.crunchbase.com/organization/runloop-ai (founded 2024); https://venturebeat.com/ai/runloop-lands-7m-to-power-ai-coding-agents-with-cloud-based-devboxes (accessed 2026-06-07)
- status: active [confirmed], source: https://runloop.ai/ (accessed 2026-06-07)
- hq_location: San Francisco, CA, USA [confirmed], source: https://www.prnewswire.com/news-releases/runloop-raises-7m-seed-round-to-bring-enterprise-grade-infrastructure-to-ai-coding-agents-302516898.html (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: ~16-17 employees (Tracxn 16 as of 2026-01-31; PitchBook 17; press cited 12 in Jul 2025) [reported], source: https://tracxn.com/d/companies/runloopai (accessed 2026-06-07; 16 as of 2026-01-31); https://pitchbook.com/profiles/company/629631-73 (17); press release 12 (Jul 2025). Note: startupintros aggregator showed an erroneous 1,001-5,000 LinkedIn band, disregarded.
- headcount_band: 11-50 [reported], source: https://tracxn.com/d/companies/runloopai (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown]
- has_researchers: no [estimated], source: https://runloop.ai/about (accessed 2026-06-07; team described as infrastructure engineers from Google, Stripe, Vercel, AWS, Meta, Scale AI; no research/PhD scientists noted)
- researcher_count: unknown [unknown]
- researcher_backgrounds: Founder/CEO Jonathan Wall: ex-Google (co-founded Google Wallet), co-founded Index (acquired by Stripe); deeper Google File System / Founders Award detail is vendor-stated; Senior engineers are alumni of Google, Stripe, Vercel, AWS, Meta, and Scale AI (per press) [reported], source: https://runloop.ai/about (accessed 2026-06-07); https://venturebeat.com/ai/runloop-lands-7m-to-power-ai-coding-agents-with-cloud-based-devboxes (accessed 2026-06-07)
- published_papers_or_benchmarks: No Runloop-authored papers/benchmarks found. Platform supports running third-party academic coding benchmarks: SWE-Bench, R2E-Gym, SWE-Smith, Multi-SWE (these are external benchmarks, not Runloop publications) [reported], source: https://runloop.ai/ (accessed 2026-06-07)
- total_raised: $7M [confirmed], source: https://www.prnewswire.com/news-releases/runloop-raises-7m-seed-round-to-bring-enterprise-grade-infrastructure-to-ai-coding-agents-302516898.html (accessed 2026-06-07); corroborated by Crunchbase ($7M, 1 round)
- last_round: Seed, $7M, 2025-07-30 [confirmed], source: https://www.crunchbase.com/funding_round/runloop-ai-seed--bd4cd02b (accessed 2026-06-07); https://www.prnewswire.com/news-releases/runloop-raises-7m-seed-round-to-bring-enterprise-grade-infrastructure-to-ai-coding-agents-302516898.html
- notable_investors: The General Partnership (lead); Blank Ventures; Exponent Founders Capital; Nascent; Roneil Rumburg (angel) [reported], source: Official press names only The General Partnership (lead) + Blank Ventures: https://www.prnewswire.com/news-releases/runloop-raises-7m-seed-round-to-bring-enterprise-grade-infrastructure-to-ai-coding-agents-302516898.html. Additional participants (Exponent Founders Capital, Nascent, Roneil Rumburg; AWS Startups per one source) listed only on aggregators: https://www.crunchbase.com/organization/runloop-ai, https://startupintros.com/orgs/runloop-ai (accessed 2026-06-07)
- valuation: unknown [unknown], source: Not publicly disclosed (Crunchbase financials obfuscated as of 2026-06-07)
- revenue_signals: Vendor-claimed: >200% customer growth and >100% revenue growth since March 2025; 'a few dozen customers' [reported], source: https://venturebeat.com/ai/runloop-lands-7m-to-power-ai-coding-agents-with-cloud-based-devboxes (accessed 2026-06-07; figures self-reported by vendor)
- soc2: claimed-unverified [reported], source: Vendor states 'SOC2 certified' on homepage and press (https://runloop.ai/, https://www.prnewswire.com/news-releases/runloop-unveils-enterprise-grade-sandboxes-for-ai-coding-agents-302460834.html, accessed 2026-06-07) but no report type, audit registry entry, or independent attestation located
- other_certifications: HIPAA (vendor-claimed); GDPR (vendor-claimed) [reported], source: https://runloop.ai/ (accessed 2026-06-07; 'HIPAA Compliant' badge, GDPR support); https://www.prnewswire.com/news-releases/runloop-raises-7m-seed-round-to-bring-enterprise-grade-infrastructure-to-ai-coding-agents-302516898.html. No independent attestation found; vendor self-claims.
- security_page: unknown [unknown], source: No dedicated public trust/security portal located as of 2026-06-07
- what_they_sell: infra [confirmed], source: https://runloop.ai/ (accessed 2026-06-07); https://docs.runloop.ai/docs/devboxes/overview
- open_source: yes (SDKs/CLI only; core platform proprietary) [confirmed], source: https://github.com/runloopai (accessed 2026-06-07; MIT-licensed TS and Python SDKs, CLI)
- license: MIT (SDKs/CLI; core platform is proprietary/closed-source) [confirmed], source: https://github.com/runloopai (accessed 2026-06-07)
- deployment_model: managed-hosted / API (VPC deployment option claimed for enterprise) [confirmed], source: https://docs.runloop.ai/docs/devboxes/overview (accessed 2026-06-07); https://runloop.ai/ (VPC option)
- maturity: GA [confirmed], source: https://www.prnewswire.com/news-releases/runloop-unveils-enterprise-grade-sandboxes-for-ai-coding-agents-302460834.html (accessed 2026-06-07; Devboxes GA announced 2025-05-20)
- notable_customers: Trajectory (vendor case study; ran ~10,000 concurrent devboxes) (self-claimed); Detail.dev (CEO quote in vendor press release) (self-claimed); ION (YC-backed) (self-claimed); Accrual (self-claimed); Unnamed 'major model laboratories' (vendor claim; no specific lab named, no third-party confirmation) (self-claimed, frontier-lab tie) [reported], source: https://runloop.ai/ (accessed 2026-06-07); https://www.prnewswire.com/news-releases/runloop-raises-7m-seed-round-to-bring-enterprise-grade-infrastructure-to-ai-coding-agents-302516898.html; https://venturebeat.com/ai/runloop-lands-7m-to-power-ai-coding-agents-with-cloud-based-devboxes. All customer mentions trace to vendor site/press; the 'model laboratories' tie is an unverified vendor assertion.
- sources:
  - https://runloop.ai/ (accessed 2026-06-07)
  - https://runloop.ai/about (accessed 2026-06-07)
  - https://docs.runloop.ai/docs/devboxes/overview (accessed 2026-06-07)
  - https://www.prnewswire.com/news-releases/runloop-raises-7m-seed-round-to-bring-enterprise-grade-infrastructure-to-ai-coding-agents-302516898.html (accessed 2026-06-07)
  - https://www.prnewswire.com/news-releases/runloop-unveils-enterprise-grade-sandboxes-for-ai-coding-agents-302460834.html (accessed 2026-06-07)
  - https://venturebeat.com/infrastructure/runloop-lands-7m-to-power-ai-coding-agents-with-cloud-based-devboxes (accessed 2026-06-07)
  - https://www.crunchbase.com/funding_round/runloop-ai-seed--bd4cd02b (accessed 2026-06-07)
  - https://www.crunchbase.com/organization/runloop-ai (accessed 2026-06-07)
  - https://github.com/runloopai (accessed 2026-06-07)
  - https://tracxn.com/d/companies/runloopai (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/629631-73 (accessed 2026-06-07)

## General Reasoning (not ranked, incumbent / infrastructure / open-source)
- slug: general-reasoning
- segment: Open-source & open environments
- website: https://www.gr.inc/
- focus_areas: Coding, Long-Horizon
- positioning: General Reasoning is an AI research lab (operating research hub in London; legal entity General Reasoning, Inc. registered in the US) building open RL environments and infrastructure for training and evaluating agents over long horizons. Its OpenReward platform and Open Reward Standard (ORS) provide an open specification for connecting language models to community-built RL environments, with 330+ environments accessible through one API.
- best_fit: Teams wanting open, portable RL environments and long-horizon agent benchmarks they can run anywhere (self-hosted) or via managed/API hosting.
- overall_confidence: medium
- founded_year: 2025 [confirmed], source: https://uk.linkedin.com/company/general-reasoning (accessed 2026-06-07); https://www.gr.inc/careers (Chapter I Founded 2025); SEC Form D filed 2025-07-11 https://www.formds.com/issuers/general-reasoning-inc
- status: active [confirmed], source: https://www.gr.inc/careers (accessed 2026-06-07); actively hiring, recent product launches
- hq_location: London, United Kingdom (Shoreditch), operating research hub; legal entity General Reasoning, Inc. registered in San Francisco/US per SEC Form D [confirmed], source: https://www.gr.inc/careers (accessed 2026-06-07); https://uk.linkedin.com/company/general-reasoning; https://www.formds.com/issuers/general-reasoning-inc
- other_locations: unknown [reported], source: https://www.gr.inc/careers (accessed 2026-06-07); only London 'Chapter I' currently exists, additional chapters 'coming soon'
- distributed_remote: no [estimated], source: https://www.gr.inc/careers (accessed 2026-06-07); all roles tied to London chapter, geographic-chapter model emphasizes in-person community
- current_headcount: ~10 (LinkedIn public snippet; '11-50' band) [reported], source: https://uk.linkedin.com/company/general-reasoning (accessed 2026-06-07)
- headcount_band: 11-50 [reported], source: https://uk.linkedin.com/company/general-reasoning (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: 3 [confirmed], source: https://www.gr.inc/careers (accessed 2026-06-07); 3 Member of Technical Staff roles (Head of Rollouts, Infrastructure, Research Scientist)
- has_researchers: yes [confirmed], source: https://www.gr.inc/research (accessed 2026-06-07)
- researcher_count: ~6 named individuals on site (founders + research/eng staff); counted from research/team page [estimated], source: https://www.gr.inc/research (accessed 2026-06-07)
- researcher_backgrounds: Ross Taylor (co-founder/CEO) - ex-Meta AI/FAIR, research lead on Galactica, led reasoning for Llama 2/Llama 3; co-founded Papers with Code (acquired by Meta); Founding team previously led open language model development at Meta (Galactica, Llama 2, Llama 3); Other named staff/directors: Kip Parker, Chengxi Wang, Thomas Grady, Iliyan Zarov, Henry Course [reported], source: https://www.gr.inc/ ; https://www.linkedin.com/in/rosstaylor90/ ; https://www.interconnects.ai/p/interviewing-ross-taylor-on-llm-reasoning (accessed 2026-06-07)
- published_papers_or_benchmarks: KellyBench: long-horizon sequential decision-making benchmark - https://www.gr.inc/releases/introducing-kellybench; OpenReward / Open Reward Standard - https://www.gr.inc/releases/introducing-openreward; Galactica, Llama 2, Llama 3 (founders' prior work at Meta) [confirmed], source: https://www.gr.inc/releases/introducing-kellybench ; https://www.gr.inc/releases/introducing-openreward (accessed 2026-06-07)
- total_raised: ~$10.9M (amount sold per SEC Form D 2025-07-11; corroborated by Crunchbase) [reported], source: https://www.formds.com/issuers/general-reasoning-inc (accessed 2026-06-07); Crunchbase profile
- last_round: Equity offering, $10,904,992 sold, filed 2025-07-11 (SEC Form D; stage not labeled, reported as ~2025 seed-stage by Crunchbase) [reported], source: https://www.formds.com/issuers/general-reasoning-inc (accessed 2026-06-07); Crunchbase lists $10.9M Aug 2025
- notable_investors: unknown [unknown], source: Form D does not name investors; no credible press disclosure found (note: a $10M 'General Analysis' seed is a different, unrelated company)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: environments [confirmed], source: https://www.gr.inc/releases/introducing-openreward (accessed 2026-06-07)
- open_source: yes [confirmed], source: https://www.gr.inc/releases/introducing-openreward (accessed 2026-06-07); Open Reward Standard described as open-source specification, openrewardstandard.io
- license: Apache-2.0 (firehorse harness repo); Open Reward Standard described as open-source, specific license not stated [reported], source: https://github.com/GeneralReasoning (accessed 2026-06-07)
- deployment_model: managed-hosted / self-hosted / API [confirmed], source: https://www.gr.inc/releases/introducing-openreward (accessed 2026-06-07)
- maturity: GA [estimated], source: https://www.gr.inc/releases/introducing-openreward (accessed 2026-06-07); OpenReward live with 330+ environments and on-demand API
- notable_customers: NVIDIA (self-claimed, frontier-lab tie); Nebius (self-claimed); Eigent (self-claimed); OpenAI (self-claimed, frontier-lab tie); Meta (self-claimed, frontier-lab tie) [reported], source: https://www.gr.inc/releases/introducing-openreward (accessed 2026-06-07); names appear as environment providers/contributors on OpenReward page (NVIDIA Nemotron envs, Nebius SWE-rebench, Eigent SETA, OpenAI MLE-bench, Meta GAIA), NOT confirmed paying customers
- sources:
  - https://www.gr.inc/ (accessed 2026-06-07)
  - https://www.gr.inc/careers (accessed 2026-06-07)
  - https://www.gr.inc/research (accessed 2026-06-07)
  - https://www.gr.inc/releases/introducing-openreward (accessed 2026-06-07)
  - https://www.gr.inc/releases/introducing-kellybench (accessed 2026-06-07)
  - https://uk.linkedin.com/company/general-reasoning (accessed 2026-06-07)
  - https://www.formds.com/issuers/general-reasoning-inc (accessed 2026-06-07)
  - https://github.com/GeneralReasoning (accessed 2026-06-07)
  - https://www.linkedin.com/in/rosstaylor90/ (accessed 2026-06-07)
  - https://www.interconnects.ai/p/interviewing-ross-taylor-on-llm-reasoning (accessed 2026-06-07)
  - https://huggingface.co/GeneralReasoning (accessed 2026-06-07)

## Cua (not ranked, incumbent / infrastructure / open-source)
- slug: cua
- segment: Adjacent: execution infrastructure
- website: https://cua.ai/
- focus_areas: Computer Use
- positioning: Cua (trycua, YC X25) is open-source MIT-licensed infrastructure for computer-use agents, providing cloud and self-hosted sandboxes across macOS, Windows, Linux, and Android plus an SDK, a virtualization layer (Lume), and a benchmarking/RL-eval suite (Cua-Bench). It positions itself as the 'Docker for computer-use agents,' giving any agent a cloud desktop.
- best_fit: Teams needing on-demand sandboxed desktop/OS environments to run, evaluate, or generate RL trajectories for computer-use agents.
- overall_confidence: medium
- founded_year: 2025 [confirmed], source: https://www.ycombinator.com/companies/cua (accessed 2026-06-07)
- status: active [confirmed], source: https://cua.ai/ (accessed 2026-06-07); https://github.com/trycua/cua (accessed 2026-06-07)
- hq_location: San Francisco, CA, USA [reported], source: https://www.ycombinator.com/companies/cua (lists SF; accessed 2026-06-07). Note: Tracxn lists Dover, DE (likely state of incorporation), so a single authoritative HQ is not fully resolved.
- other_locations: unknown [unknown]
- distributed_remote: unknown [unknown]
- current_headcount: ~3-10 (YC lists team size 3; LinkedIn shows 2-10 band) [reported], source: https://www.ycombinator.com/companies/cua (team size 3; accessed 2026-06-07); https://www.linkedin.com/company/cua-ai (2-10 band; accessed 2026-06-07)
- headcount_band: 1-10 [reported], source: https://www.linkedin.com/company/cua-ai (2-10 band; accessed 2026-06-07); https://www.ycombinator.com/companies/cua (team size 3; accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: 2 (Research Intern Summer 2026; Founding Engineer, Infra & Agent Systems) [reported], source: https://www.ycombinator.com/companies/cua (accessed 2026-06-07)
- has_researchers: yes [reported], source: https://www.ycombinator.com/companies/cua (Research Intern role; accessed 2026-06-07); https://github.com/trycua/cua (Cua-Bench RL/eval work; accessed 2026-06-07)
- researcher_count: unknown [unknown]
- researcher_backgrounds: Francesco Bonacci, co-founder, previously at Xbox / Microsoft AI; Alessandro Puppo, co-founder (background not detailed in public sources) [reported], source: https://www.ycombinator.com/companies/cua (Bonacci, ex-Xbox/Microsoft AI; accessed 2026-06-07); Tracxn / LinkedIn list Alessandro Puppo as co-founder (accessed 2026-06-07)
- published_papers_or_benchmarks: Cua-Bench (benchmarking suite / RL environments; runs OSWorld, ScreenSpot, Windows Arena, exports RL training trajectories), https://cuabench.ai / https://github.com/trycua/cua [reported], source: https://github.com/trycua/cua (Cua-Bench component; accessed 2026-06-07); https://cuabench.ai/ (per draft, accessed 2026-06-07). This is a vendor benchmarking/eval product, not a peer-reviewed paper.
- total_raised: ~$500K (pre-seed/seed, ~June 2025) [reported], source: https://tracxn.com/d/companies/cua-ai (aggregator; accessed 2026-06-07); https://www.linkedin.com/company/cua-ai (accessed 2026-06-07). No primary press release or official funding announcement located; figure rests on aggregators only.
- last_round: Pre-seed/seed, ~$500K, ~June 2025 [reported], source: https://tracxn.com/d/companies/cua-ai (lists ~$500K, round ~June 2025; accessed 2026-06-07). Round-type label (pre-seed vs seed) and exact date inconsistent across aggregator snippets; no primary announcement found.
- notable_investors: Y Combinator (X25 batch) [reported], source: https://www.ycombinator.com/companies/cua (YC X25 batch membership confirmed; accessed 2026-06-07). YC as a named round investor is corroborated only by aggregators; no primary round announcement located.
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown], source: https://cua.ai/ and https://cua.ai/pricing (no compliance/SOC2 mentions found; accessed 2026-06-07)
- other_certifications: unknown [unknown]
- security_page: unknown [unknown], source: No dedicated trust/security page found on cua.ai (accessed 2026-06-07)
- what_they_sell: infra [confirmed], source: https://cua.ai/ (accessed 2026-06-07); https://github.com/trycua/cua (accessed 2026-06-07)
- open_source: yes [confirmed], source: https://github.com/trycua/cua (accessed 2026-06-07)
- license: MIT [confirmed], source: https://github.com/trycua/cua (MIT License; accessed 2026-06-07)
- deployment_model: managed-hosted (Cua Cloud) + self-hosted/on-prem (Enterprise On-Prem, Lume local) + API/SDK [confirmed], source: https://cua.ai/pricing (accessed 2026-06-07); https://cua.ai/ (accessed 2026-06-07)
- maturity: GA (Free, Pro from $10/mo, and Enterprise plans publicly available; Cua Driver in pre-release) [confirmed], source: https://cua.ai/pricing (accessed 2026-06-07); https://github.com/trycua/cua (accessed 2026-06-07)
- notable_customers: Hugging Face (self-claimed); Datadog (self-claimed); Meta (self-claimed, frontier-lab tie); Elastic (self-claimed); Apple (self-claimed); Red Hat (self-claimed); NVIDIA (self-claimed); Duolingo (self-claimed) [reported], source: https://cua.ai/ ('Trusted by 50,000+ engineers at your favorite companies' logo wall, self-claimed; presented as organizations whose engineers use the OSS, not verified paying customers; accessed 2026-06-07)
- sources:
  - https://www.ycombinator.com/companies/cua (accessed 2026-06-07)
  - https://github.com/trycua/cua (accessed 2026-06-07)
  - https://cua.ai/ (accessed 2026-06-07)
  - https://cua.ai/pricing (accessed 2026-06-07)
  - https://www.linkedin.com/company/cua-ai (accessed 2026-06-07)
  - https://tracxn.com/d/companies/cua-ai (accessed 2026-06-07)
  - https://cuabench.ai/ (accessed 2026-06-07)
  - https://news.ycombinator.com/item?id=43773563 (accessed 2026-06-07)
  - https://www.linkedin.com/in/francesco-bonacci-70428a121/ (accessed 2026-06-07)
  - https://www.linkedin.com/in/alessandro-puppo/ (accessed 2026-06-07)

## Good Start Labs (not ranked, incumbent / infrastructure / open-source)
- slug: good-start-labs
- segment: Open-source & open environments
- website: https://goodstartlabs.com
- focus_areas: Long-Horizon
- positioning: Good Start Labs is a 2025 Every spin-out that builds game-based environments to generate reinforcement-learning data and evaluate frontier models, using both custom games and partnerships with existing games where player behavior helps train and rank AI. It is known for AI Diplomacy / Diplomacy Arena (multi-agent long-horizon strategy) and LOL Arena (humor preference), and publishes openly on GitHub and Hugging Face.
- best_fit: Buyers wanting open, game-based RL environments and benchmarks for long-horizon multi-agent reasoning and preference/humor evaluation.
- overall_confidence: medium
- founded_year: 2025 [confirmed], source: https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07); https://every.to/on-every/our-new-incubation-raised-3-6-million-to-teach-ais-to-play-games (accessed 2026-06-07)
- status: active [confirmed], source: https://goodstartlabs.com/ (accessed 2026-06-07); https://github.com/GoodStartLabs (accessed 2026-06-07); https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07)
- hq_location: Brooklyn, NY, USA [reported], source: https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07)
- other_locations: Toronto, ON, Canada [reported], source: https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07)
- distributed_remote: yes [estimated], source: https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07), HQ Brooklyn with Toronto office; cross-border US/Canada team implies distributed; startups.gallery lists remote but is low-reliability
- current_headcount: ~9-10 (as of 2026-06-07) [reported], source: https://huggingface.co/GoodStartLabs (9 team members, accessed 2026-06-07); LinkedIn company page public snippet (size 2-10, accessed 2026-06-07)
- headcount_band: 1-10 [reported], source: https://huggingface.co/GoodStartLabs (9 team members, accessed 2026-06-07); LinkedIn public snippet (size 2-10, accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: https://goodstartlabs.com/careers (careers page exists; direct fetch returned 403; exact count not confirmed, accessed 2026-06-07)
- has_researchers: yes [reported], source: https://huggingface.co/GoodStartLabs (research model/dataset publishing, accessed 2026-06-07); https://github.com/GoodStartLabs (research benchmarks, accessed 2026-06-07)
- researcher_count: unknown [unknown]
- researcher_backgrounds: Alex Duffy (Co-Founder & CEO), ex-Head of AI Training at Every; creator of AI Diplomacy; background in AI training/education (AI Camp); prior ML work; Tyler Marques (Co-Founder & CTO), University of Waterloo; applied AI/ML/DevOps background [reported], source: https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07); https://every.to/p/diplomacy (Alex Duffy bio, accessed 2026-06-07); https://ca.linkedin.com/in/tylermarques (accessed 2026-06-07)
- published_papers_or_benchmarks: AI Diplomacy / Diplomacy Arena, frontier models playing the board game Diplomacy (github.com/GoodStartLabs/AI_Diplomacy); LOL Arena, humor preference benchmark informed by human votes; GSLBenchmark / gsl-benchmark-logs (Hugging Face datasets); OpenTinker, RL infrastructure repo (Apache-2.0) [reported], source: https://github.com/GoodStartLabs (accessed 2026-06-07); https://huggingface.co/GoodStartLabs (accessed 2026-06-07); https://every.to/p/diplomacy (accessed 2026-06-07)
- total_raised: $3.6M [reported], source: https://every.to/on-every/our-new-incubation-raised-3-6-million-to-teach-ais-to-play-games (accessed 2026-06-07); https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07)
- last_round: Seed, $3.6M, October 2025 (Inovia describes it as pre-seed) [reported], source: https://every.to/on-every/our-new-incubation-raised-3-6-million-to-teach-ais-to-play-games (accessed 2026-06-07); https://www.inovia.vc/active-companies/good-start-labs/ (pre-seed, Oct 2025, accessed 2026-06-07); https://www.linkedin.com/posts/tirtavc_were-thrilled-to-announce-tirta-ventures-activity-7384641634371608576-pf7K (seed, accessed 2026-06-07)
- notable_investors: General Catalyst; Inovia Capital; Tirta Ventures; Every; angel investors from top AI labs (incl. DeepMind alumni) [reported], source: https://every.to/on-every/our-new-incubation-raised-3-6-million-to-teach-ais-to-play-games (General Catalyst, Inovia, Every, DeepMind angels, accessed 2026-06-07); https://www.linkedin.com/posts/tirtavc_were-thrilled-to-announce-tirta-ventures-activity-7384641634371608576-pf7K (Tirta Ventures co-lead, accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: environments [reported], source: https://every.to/on-every/our-new-incubation-raised-3-6-million-to-teach-ais-to-play-games (accessed 2026-06-07); https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07)
- open_source: yes [confirmed], source: https://github.com/GoodStartLabs (accessed 2026-06-07); https://github.com/GoodStartLabs/AI_Diplomacy (accessed 2026-06-07)
- license: Apache-2.0 (OpenTinker repo); AI_Diplomacy repo license not specified [reported], source: https://github.com/GoodStartLabs (accessed 2026-06-07)
- deployment_model: unknown [unknown]
- maturity: research preview [estimated], source: https://github.com/GoodStartLabs (accessed 2026-06-07), open arenas/benchmarks (Diplomacy Arena, LOL Arena) and OSS repos; early-stage 2025 spin-out
- notable_customers: Bad Cards (Discord Cards-Against-Humanity-style game; LOL Arena partnership / data source) (self-claimed) [reported], source: https://every.to/on-every/our-new-incubation-raised-3-6-million-to-teach-ais-to-play-games (accessed 2026-06-07), described as a game partnership, not a paying customer; no third-party confirmation
- sources:
  - https://goodstartlabs.com/about (accessed 2026-06-07)
  - https://goodstartlabs.com/careers (accessed 2026-06-07)
  - https://github.com/GoodStartLabs (accessed 2026-06-07)
  - https://huggingface.co/GoodStartLabs (accessed 2026-06-07)
  - https://www.inovia.vc/active-companies/good-start-labs/ (accessed 2026-06-07)
  - https://www.inovia.vc/founders/company-founders/tyler-marques/ (accessed 2026-06-07)
  - https://every.to/on-every/our-new-incubation-raised-3-6-million-to-teach-ais-to-play-games (accessed 2026-06-07)
  - https://tracxn.com/d/companies/goodstartlabs/funding-and-investors (accessed 2026-06-07)
  - https://www.linkedin.com/company/good-start-labs (accessed 2026-06-07)
  - https://startups.gallery/companies/good-start-labs (accessed 2026-06-07)
  - https://every.to/diplomacy (accessed 2026-06-07)

## Morph (not ranked, incumbent / infrastructure / open-source)
- slug: morph
- segment: Adjacent: execution infrastructure
- website: https://www.morph.so
- focus_areas: Coding
- positioning: Morph (Morph Labs) provides snapshot-based VM compute for AI agents via its Infinibranch / Liquid Metal technology, which can snapshot, branch, and restore entire computational environments in roughly 100-250ms to enable massively parallel, reversible ('Git for compute') agent rollouts, evaluations, and reasoning-time branching. It markets the platform (Morph Cloud) as infrastructure for running and scaling agent/RL verification environments rather than as an RL-environment dataset vendor itself.
- best_fit: Teams needing to fork, snapshot, and run thousands of parallel/reversible sandboxed VM environments for agent rollouts, evals, and verification at scale.
- overall_confidence: medium
- founded_year: 2023 [reported], source: https://tracxn.com/d/companies/morph-labs (accessed 2026-06-07); https://www.cbinsights.com/company/morph-labs (accessed 2026-06-07)
- status: active [confirmed], source: https://cloud.morph.so/docs/developers (accessed 2026-06-07); https://x.com/morph_labs/status/1966223824078479667 (Math Inc incubation announcement, accessed 2026-06-07)
- hq_location: San Francisco, USA [reported], source: https://www.cbinsights.com/company/morph-labs (accessed 2026-06-07); https://tracxn.com/d/companies/morph-labs (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: yes [reported], source: https://www.morph.so/careers (accessed 2026-06-07), remote roles indicated
- current_headcount: ~9-11 employees (as of 2026) [estimated], source: https://rocketreach.co/morph-labs-management_b7384e18c7e2a4d3 (accessed 2026-06-07, ~9); https://pitchbook.com/profiles/company/44794-09 (accessed 2026-06-07, ~11)
- headcount_band: 1-10 [estimated], source: https://rocketreach.co/morph-labs-management_b7384e18c7e2a4d3 (accessed 2026-06-07), borderline with 11-50 per PitchBook (~11)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown], source: https://www.morph.so/careers (accessed 2026-06-07), careers page exists and is actively recruiting researcher-engineers, but exact count not extractable (JS-rendered)
- has_researchers: yes [confirmed], source: https://www.morph.so/blog/liquid-metal (accessed 2026-06-07); https://github.com/morph-labs (accessed 2026-06-07)
- researcher_count: unknown (small team; at least CEO Jesse Han and Chief Scientist Christian Szegedy plus members of technical staff) [estimated], source: https://rocketreach.co/morph-labs-management_b7384e18c7e2a4d3 (accessed 2026-06-07)
- researcher_backgrounds: Jesse Han, founder/CEO; PhD work in formal mathematics (formalized independence of the continuum hypothesis in Lean); ex-OpenAI / Microsoft Research / AWS per profiles; Christian Szegedy, Chief Scientist; ex-xAI co-founder (Grok-3 code reasoning lead), ex-Google Research (deep learning/Inception, BatchNorm, adversarial examples, autoformalization) [reported], source: https://www.theinformation.com/briefings/xai-cofounder-joins-ai-code-startup-morph-chief-scientist (accessed 2026-06-07); https://www.startuphub.ai/ai-news/ai-video/2025/morph-labs-unveils-liquid-metal-powering-the-agentic-future (accessed 2026-06-07)
- published_papers_or_benchmarks: Trinity, autoformalization system for verified superintelligence (Morph Labs blog); Morph Prover v0 7B, open-source model (early Morph Labs work); SWELancer-Benchmark setup on Morph Cloud (github.com/morph-labs/SWELancer-Benchmark); open-r1 reproduction (github.com/morph-labs/open-r1) [reported], source: https://github.com/morph-labs (accessed 2026-06-07); https://www.math.inc/gauss (accessed 2026-06-07)
- total_raised: unknown [unknown], source: Tracxn lists Morph Labs (Jesse Han) as 'Unfunded / has not raised any funding rounds yet' (accessed 2026-06-07). A seed/angel investment by Christian Szegedy is reported but amount undisclosed. NOTE: the widely-cited '$19-20M seed' (Crunchbase round 875f78ba, led by Dragonfly Capital, 2024-03-20) belongs to the unrelated Morph Ethereum L2 / blockchain project, NOT this company.
- last_round: unknown [unknown]
- notable_investors: Christian Szegedy (reported seed/angel investor; also Chief Scientist), amount undisclosed [reported], source: https://www.cogniscendo.com/p/the-superhuman-mathematician-5d1b (accessed 2026-06-07)
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: claimed-unverified [reported], source: https://trust.delve.co/morph (accessed 2026-06-07), trust portal snippet indicates a SOC 2 Type 2 report for 2025, but the portal is hosted by Delve, which in March 2026 was the subject of a TechCrunch/Substack investigation alleging fabrication of ~494 SOC 2 reports (allegations denied/unproven). Direct fetch returned 403/429; no independent audit-firm confirmation obtained. Treat as claimed-unverified pending independent verification.
- other_certifications: unknown [unknown], source: https://trust.delve.co/morph (accessed 2026-06-07), no ISO 27001 / HIPAA confirmed
- security_page: https://trust.delve.co/morph [reported], source: https://trust.delve.co/morph (accessed 2026-06-07)
- what_they_sell: infra [confirmed], source: https://cloud.morph.so/docs/developers (accessed 2026-06-07); https://www.morph.so/blog/infinibranch/ (accessed 2026-06-07)
- open_source: yes [confirmed], source: https://github.com/morph-labs (accessed 2026-06-07), SDKs (morph-python-sdk, morph-typescript-sdk) and examples are Apache-2.0/MIT; core Infinibranch/Liquid Metal platform is proprietary
- license: Apache-2.0 (SDKs and morphcloud-examples-public); MIT (some example repos). Core platform proprietary. [confirmed], source: https://github.com/morph-labs (accessed 2026-06-07)
- deployment_model: managed-hosted (cloud platform, accessed via Python/TypeScript SDK, CLI, and API keys) [confirmed], source: https://cloud.morph.so/docs/developers (accessed 2026-06-07)
- maturity: GA [estimated], source: https://cloud.morph.so/docs/developers (accessed 2026-06-07), public self-serve signup, SDKs, and docs available; no explicit GA label found
- notable_customers: Math Inc (Math, Inc.), used Morph Cloud / Infinibranch to scale Lean verification environments for its Gauss autoformalization agent; company incubated at Morph (closely tied entity, not arm's-length customer) (self-claimed) [reported], source: https://x.com/morph_labs/status/1966223824078479667 (accessed 2026-06-07); https://www.math.inc/gauss (accessed 2026-06-07)
- sources:
  - https://www.morph.so/ (accessed 2026-06-07)
  - https://cloud.morph.so/docs/developers (accessed 2026-06-07)
  - https://www.morph.so/blog/infinibranch/ (accessed 2026-06-07)
  - https://www.morph.so/blog/liquid-metal (accessed 2026-06-07)
  - https://www.startuphub.ai/ai-news/ai-video/2025/morph-labs-unveils-liquid-metal-powering-the-agentic-future (accessed 2026-06-07)
  - https://github.com/morph-labs (accessed 2026-06-07)
  - https://x.com/morph_labs/status/1966223824078479667 (accessed 2026-06-07)
  - https://www.math.inc/gauss (accessed 2026-06-07)
  - https://www.cogniscendo.com/p/the-superhuman-mathematician-5d1b (accessed 2026-06-07)
  - https://www.theinformation.com/briefings/xai-cofounder-joins-ai-code-startup-morph-chief-scientist (accessed 2026-06-07)
  - https://trust.delve.co/morph (accessed 2026-06-07)
  - https://tracxn.com/d/companies/morph-labs/__8ZZWlPNWnRct4CJf-JJjU940HzzVxh1CEZxBQBG6tXg (accessed 2026-06-07)
  - https://pitchbook.com/profiles/company/44794-09 (accessed 2026-06-07)
  - https://rocketreach.co/morph-labs-management_b7384e18c7e2a4d3 (accessed 2026-06-07)
  - https://www.cbinsights.com/company/morph-labs (accessed 2026-06-07)
  - https://www.morph.so/careers (accessed 2026-06-07)
  - https://www.morphllm.com/ (accessed 2026-06-07)

## Turing (not ranked, incumbent / infrastructure / open-source)
- slug: turing
- segment: Incumbents also building RL environments
- website: https://www.turing.com/
- focus_areas: Coding, Enterprise Workflows, Private Codebases
- positioning: Turing is a large AGI-infrastructure and engineering-services company that supplies frontier AI labs with coding data, human expertise, and RL/evaluation data at scale, drawing on a global vetted developer and domain-expert network. Originally a remote-engineering talent marketplace, it now positions itself around 'AGI advancement' through code and reasoning data, including work over private/real codebases.
- best_fit: Buyers needing very large-scale human coding and reasoning data, expert labor, and evaluations over real codebases from an established incumbent rather than a focused environment startup.
- overall_confidence: low
- founded_year: 2018 [reported], source: Widely reported founding year (Jonathan Siddharth & Vijay Krishnan); accessed 2026-06-07
- status: active [confirmed], source: https://www.turing.com/ (accessed 2026-06-07)
- hq_location: Palo Alto, USA [reported], source: Public company profiles (accessed 2026-06-07)
- other_locations: unknown [unknown]
- distributed_remote: yes [reported], source: Turing operates a global remote engineering/expert network (accessed 2026-06-07)
- current_headcount: unknown [unknown]
- headcount_band: 200+ [reported], source: Large organization with a global contractor/expert network (accessed 2026-06-07)
- headcount_growth: unknown [unknown]
- open_roles_count: unknown [unknown]
- has_researchers: yes [reported], source: Turing AGI/research org and expert network (accessed 2026-06-07)
- researcher_count: unknown [unknown]
- researcher_backgrounds: unknown [unknown]
- published_papers_or_benchmarks: unknown [unknown]
- total_raised: unknown [unknown], source: Added 2026-06-07; funding figures pending verification, not estimated here to avoid an unsourced number
- last_round: unknown [unknown]
- notable_investors: unknown [unknown]
- valuation: unknown [unknown]
- revenue_signals: unknown [unknown]
- soc2: unknown [unknown]
- other_certifications: unknown [unknown]
- security_page: unknown [unknown]
- what_they_sell: human data [reported], source: https://www.turing.com/, supplies frontier labs with coding/reasoning data, human expertise, and evaluations (accessed 2026-06-07)
- open_source: no [estimated], source: No public RL-environment OSS identified (accessed 2026-06-07)
- license: unknown [unknown]
- deployment_model: unknown [unknown]
- maturity: GA [reported], source: Established commercial company (accessed 2026-06-07)
- notable_customers: unknown [unknown], source: Turing publicly states it works with leading AI labs but does not name them in citable form (accessed 2026-06-07)
- sources:
  - https://www.turing.com/ (accessed 2026-06-07)