Proximal

Commercial

medium confidence

www.proximal.ai ↗ · Status: active confirmed · Founded 2026

Proximal is a research lab in San Francisco and Bangalore that treats post-training data as a core research problem. It builds long-horizon coding RL environments and data for frontier labs and enterprises, and it publishes the FrontierSWE benchmark and verifier audits such as CyberGym-Verified. In September 2026 it raised a $15M seed led by General Catalyst at a $300M valuation and claimed $200M in annualized revenue, which is self-reported. It also said it will expand into drug discovery, chip design and legacy software modernization.

Key facts

Headquarters

San Francisco, CA, USAconfirmed cite

Headcount band

11-50reported cite

Total raised

$15Mconfirmed cite

Last round

Seed: $15M led by General Catalyst at a $300M valuation (announced 2026-09-29)confirmed cite

SOC 2

unknown cite

What they sell

environmentsconfirmed cite

Open source

yesconfirmed cite

Deployment

unknown

What's new

7 sourced updates · last 6 months

5 Oct 2026hire Careers page lists 5 open roles across San Francisco and Bangalore
San Francisco: Software Engineer, Research Engineer, Applied Researcher. Bangalore: Software Engineer, Research Engineer. The baseline had 3 roles. This is a snapshot taken on 2026-10-05.
Why it matters: It shows modest team growth after the round.
30 Sep 2026research 'Robustly Evaluating Cyber Capabilities': Proximal audits CyberGym and releases a filtered CyberGym-Verified subset
Anish Lakkapragada describes two failure modes in CyberGym's differential-execution scoring. In the first, an agent reproduces the intended bug but it crashes both the patched and unpatched binaries (a false negative). In the second, an agent triggers a different bug that still meets the criteria (a false positive). On the filtered CyberGym-Verified set, Kimi K3 scores 95.6% pass@1, against 81.9% on the original CyberGym. On Verified, GLM 5.3 scores 93.5%, GPT-5.6 Sol 91.1% and Claude Fable 5.1/Opus 5 87.8%. Tasks were converted with a modified Harbor adapter.
Why it matters: Proximal is extending its verifier and reward-hacking auditing beyond coding into cyber evals. The near-saturated Verified scores are a warning for anyone who reports raw CyberGym numbers.
29 Sep 2026funding Proximal announces a $15M seed round led by General Catalyst at a $300M valuation and claims $200M in annualized revenue
The 'New Frontiers' post says Proximal raised '$15m at a $300m valuation', led by General Catalyst. SV Angel, Diede van Lamoen (Go Global Ventures), Chemistry and angels Liam Fedus, Kevin Weil and Erik Bernhardsson also invested. The homepage card calls it a 'Seed Fundraise'. The post states that the company was able 'to scale to $200M in annualized revenue' and plans to move beyond software engineering into drug discovery, chip design and legacy software modernization. It says the team comes from Cursor, Google DeepMind, Meta Superintelligence, Prime Intellect, Citadel and Jane Street, and that former founders make up more than half of it. No customers are named; the post refers only to 'frontier labs and enterprises'.
Why it matters: This is the first disclosed round size, lead investor and valuation. The $200M run-rate is the company's own claim and has not been independently verified. A $300M valuation on $200M of revenue is an unusually low multiple, so buyers should treat the revenue figure as a claim until a third party confirms it.
19 Sep 2026open-source px-eval open-sourced: a thin runner for Harbor tasks
This is a minimal Python runner for Harbor-format tasks. It is configured with a Harbor EnvironmentConfig (YAML/JSON) plus per-task job.yaml profiles, and runs rollouts and image preflight checks on Modal. frontier-swe-v2 is its reference task set. The repo has a single commit and was last updated 2026-09-19.
Why it matters: It confirms that Proximal's public tasks use the Harbor format and run on Modal sandboxes, which matters for data-ops integration.
Sep 2026funding The Information: 'General Catalyst Backs Coding Data Startup Proximal As It Reaches Revenue Milestone'
Stephanie Palazzolo's AI Agenda newsletter covered General Catalyst's backing and a revenue milestone. The article is paywalled, so only the headline and author could be verified, not the figures or any customer names. Bing News showed it as '5 days ago' on 2026-10-05, which puts it around 2026-09-30.
Why it matters: This is independent coverage by credible press that General Catalyst backed the company and that it hit a revenue milestone. It does not confirm the $200M figure.
Sep 2026benchmark FrontierSWE v2 released: 34 ultra-long-horizon tasks, 20-hour budgets and a new Proximus harness
v2 grows to 34 tasks, 21 of them new, across implementation, scientific computing, performance optimisation, visual reasoning and AI research. Each task has a 20-hour budget and each model gets 5 trials. Proximus is a minimal harness based on mini-swe-agent with compaction, image viewing and Git-backed submission checkpointing. Verification now runs in a separate container. The agent runs as a non-root user and scored material sits under root-owned 0700 paths. Implementation tasks are structurally mutated at verification time, and performance tasks are measured by deterministic instruction counts. The post's results: Claude Fable 5.1 56.29% (Opus 5 used as fallback on content-filter-blocked tasks), GPT-5.6 Sol 32.2%, GLM-5.3 30.2%. The repo is public at github.com/Proximal-Labs/frontier-swe-v2. Core team: 21 named authors, including all three co-founders.
Why it matters: It is one of the few public multi-hour coding evals that is hardened against cheating, and the post shows frontier models far from saturating it.
6 Jul 2026legal Public Master Development Services Agreement posted (last updated 2026-07-06)
The template MSA linked from the homepage names the contracting entity as Proximal AI, Inc. under California law with San Francisco County venue. Proximal keeps ownership of deliverables, and the customer gets a limited, non-exclusive, non-transferable, non-sublicensable licence for internal business purposes. Proximal may keep 'learnings, improvements, optimizations, or model training derived from' the work and may reuse its own materials for other customers. Liability is capped at the previous 12 months of fees, with the usual carve-outs. The MSA does not mention SOC 2.
Why it matters: Procurement and data-ops teams should note the default IP position: the data is licensed non-exclusively, not assigned to the customer. Negotiated statements of work may differ.

Founding team

Justus Mattern

Co-founder

Built open RL infrastructure at Prime Intellect, co-founded Revideo (YC S23, an open-source animation library) and was one of the first engineers at Dynamo AI (federated learning, on-device ML). Studied physics at RWTH Aachen and left in 2023. Did research on ML and differential privacy.

Profile ↗

Calvin Chen

Co-founder

Named as a co-founder in Scribble Ventures' announcement and listed as an author on the FrontierSWE v2 core team. His site says he 'invests, writes' and that the founding team includes 'second-time exited founders', but it names no specific prior company or exit.

Profile ↗

Navid Pour

Co-founder

Named as a co-founder in Scribble Ventures' announcement and listed as an author on the FrontierSWE v2 core team. Prior Cursor experience comes only from founder posts saying the team includes 'early engineers from Cursor'; no specific title is corroborated.

What practitioners should know

For researchers

FrontierSWE v2 has 34 tasks, a 20-hour budget and 5 trials per model. Its anti-reward-hacking measures are separate-container verification, a non-root agent user with root-owned 0700 scored paths, 1:1 structural mutation at verification time and deterministic instruction-count metrics for performance tasks (https://www.frontierswe.com/blog/v2).
The live v2 leaderboard has been extended beyond the models in the release post, and Fable 5.1 shows 56.5% there against 56.29% in the post. Cite the source and the access date when quoting scores.
The CyberGym audit shows that differential-execution scoring produces both false negatives and false positives. On the filtered Verified subset, several models score above 87%, which suggests the original benchmark is close to saturated.
Stated research themes are fuzzy verifiers, reward-hacking detection and long-horizon environments built from real codebases (https://www.proximal.ai/blog/our-problems/).

For program managers

Seed round of $15M led by General Catalyst at a company-stated $300M valuation, announced 2026-09-29. The Information covered it, but its article is paywalled.
The company claims $200M in annualized revenue. That figure is self-reported and unverified; The Information's headline mentions only a 'revenue milestone'.
The company says it works 'with frontier labs and enterprises' but names no customers. Kevin Weil (ex-OpenAI CPO), Liam Fedus (Periodic Labs) and Erik Bernhardsson (Modal) are angels; an angel investment does not make their companies customers.
It plans to expand beyond coding into drug discovery, chip design and legacy software modernization.
Offices are in San Francisco and Bangalore, with 5 open roles as of 2026-10-05.

For data ops

Under the public template MSA (last updated 2026-07-06), Proximal owns the deliverables and the customer gets a non-exclusive internal-use licence. Proximal may keep learnings and model training derived from the work. Negotiate exclusivity or assignment in the statement of work if you need it.
Public tasks use the Harbor format (instruction.md, task.toml, environment/Dockerfile, solution/solve.sh, preflight/). Images are pinned by digest in task.toml and can be rebuilt from each task's Dockerfile.
px-eval runs Harbor tasks on Modal and needs MODAL_TOKEN_ID and MODAL_TOKEN_SECRET plus model-provider API keys.
The frontier-swe, frontier-swe-v2 and px-eval repos show no OSS licence. v2 task content is 'provided for evaluation purposes', with upstream attributions per task.
There is no public security or trust page (/security/ and /trust/ return 404), and neither the site nor the MSA mentions SOC 2.

Benchmarks & research

3 published

CyberGym-Verified (CyberGym audit)paper · 30 Sep 2026

Proximal's audit of the third-party CyberGym vulnerability-reproduction benchmark. It finds tasks that produce false negatives and false positives under differential-execution scoring and reports a filtered 'Verified' subset. Tasks were converted with a modified Harbor adapter.

Kimi K3 scores 95.6% pass@1 on CyberGym-Verified, against 81.9% on the original. On Verified, GLM 5.3 scores 93.5%, GPT-5.6 Sol 91.1% and Claude Fable 5.1/Opus 5 87.8%.

Open ↗

FrontierSWE v2benchmark · Sep 2026

34 ultra-long-horizon coding tasks covering implementation, scientific computing, performance optimisation, visual reasoning and AI research. Each task has a 20-hour budget, each model gets 5 trials, and runs use the Proximus harness with separate-container verification and structural mutation. Tasks are in Harbor format, run via px-eval. Repo: https://github.com/Proximal-Labs/frontier-swe-v2

Release post: Claude Fable 5.1 56.29% (Opus 5 used as fallback on content-filter-blocked tasks), GPT-5.6 Sol 32.2%, GLM-5.3 30.2%. The live leaderboard, accessed 2026-10-05, now includes later models: GPT-6 Astra 65.5% ± 8.9, Claude Opus 5.5 62.3% ± 9.8, Gemini 4 Argon 55.0% ± 9.9. It shows Fable 5.1 at 56.5%, slightly different from the post.

Open ↗Paper ↗

FrontierSWE (v1)benchmark · 9 Jul 2026

Ultra-long-horizon coding agent benchmark with 17 tasks (5 implementation, 9 performance, 3 research). Each task has a 20-hour budget, each model gets 5 trials, and scoring gives partial credit from 0 to 1. Core team: Evan Chu and Rajan Agarwal (co-leads), Abishek Thangamuthu, Brendan Graham and Justus Mattern, plus 26 listed contributors. The displayed date may be reset: the baseline already cited frontierswe.com on 2026-06-07.

Claude Fable 5 ranked first on mean@5 with an average rank of 2.88. The write-up says 'the only models consistently producing at least partial solutions are GPT-5.4 in Codex and Claude Opus 4.6 in Claude Code.'

Open ↗Paper ↗

Products

Post-training data and long-horizon coding RL environments (commercial) ↗

Custom data and environments for frontier labs and enterprises training coding agents, sold under a Master Development Services Agreement. There is no public product SKU, pricing or self-serve offering, and no customers are named.

FrontierSWE (benchmark and leaderboard) ↗

Public ultra-long-horizon coding benchmark and leaderboard, now at v2 (34 tasks).launched Sep 2026

Proximus harness ↗

Minimal coding-agent harness for multi-hour tasks, described as 'essentially mini-swe-agent with small additions'. It adds context compaction, image viewing and Git-backed submission checkpointing. The post does not say whether its code is public.launched Sep 2026

px-eval ↗

Open-source thin runner for Harbor tasks that runs rollouts on Modal.launched 19 Sep 2026

Scale & velocity

Current headcount

11-50 band (LinkedIn); '~25' is an unverified estimateestimated cite

Headcount growth

unknown

Open roles

5confirmed cite

Other locations

Bangalore, Indiaconfirmed cite

Distributed / remote

noreported cite

Research depth

Has researchers

yesconfirmed cite

Researcher count

unknown

Backgrounds

Justus Mattern (co-founder): built open RL infrastructure at Prime Intellect, co-founded Revideo (YC S23), early engineer at Dynamo AI, research on ML and differential privacy (confirmed via justusmattern.com), Calvin Chen (co-founder): prior-exit specifics not corroborated, Navid Pour (co-founder): prior Cursor experience per founder posts, no specific title corroborated, Team from Cursor, Google DeepMind, Meta Superintelligence, Prime Intellect, Citadel and Jane Street; former founders are more than half the team (company-stated, 2026-09-29)reported cite

Capital

Total raised

At least $15M disclosed (2026-09 seed). The amount of the earlier Scribble Ventures-led round, if it was a separate round, is undisclosed.confirmed cite

Last round

Seed: $15M led by General Catalyst at a $300M valuation (announced 2026-09-29)confirmed cite

Investors

General Catalyst (lead, 2026-09 seed), Scribble Ventures (led an earlier investment, per its announcement), SV Angel, Go Global Ventures (Diede van Lamoen), Chemistry, Liam Fedus (CEO, Periodic Labs), Kevin Weil (former CPO, OpenAI), Erik Bernhardsson (CEO, Modal), Angels from OpenAI, Anthropic, Thinking Machines, Renaissance Technologies, Google DeepMind, xAI, Meta Superintelligence, Cursor and Cognition (per founder Calvin Chen's site; self-reported, not independently verified)confirmed cite

Valuation

$300M (company-stated, 2026-09-29)confirmed cite

Revenue signals

Company claims it was able 'to scale to $200M in annualized revenue' (2026-09-29). This is self-reported. The Information's headline refers to a 'revenue milestone' but the figure is paywalled and not independently verified.reported cite

Date	Round	Amount	Led by
29 Sep 2026	Seed	$15M valuation $300M	General Catalyst	source ↗
	Seed (labelled 'Seed Fundraise' on the proximal.ai homepage card; the post itself gives no stage label)

Security & compliance

SOC 2

unknown cite

Other certifications

unknown

Security page

unknown cite

Product

What they sell

environmentsconfirmed cite

Open source

yesconfirmed cite

License

No licence on frontier-swe, frontier-swe-v2 or px-eval. v2 task content is 'provided for evaluation purposes'.confirmed cite

Deployment model

unknown

Maturity

unknown

Notable customers

unknown

Buyer analysis

Best fit: Frontier labs or AI startups needing long-horizon, real-codebase RL environments and quality-aware (fuzzy) verifiers to post-train coding agents.

How we verified this

2026-10-05 refresh: I opened every source in the draft. The 2026-09-29 'New Frontiers' post confirms the $15M round at a $300M valuation led by General Catalyst, the other investors and the angels, the $200M annualized revenue claim and the expansion areas. The homepage card labels the round 'Seed', so I corrected the stage, and The Information's paywalled AI Agenda piece independently reports General Catalyst's backing and a revenue milestone. I confirmed the FrontierSWE v2 details (34 tasks, 21 new, 20-hour budgets, 5 trials, Proximus, hardening, results), the CyberGym audit numbers, px-eval, repo licences and star counts, the 5 careers roles and the 404 security page. I corrected the FrontierSWE v1 contributor count and the paraphrase of its partial-solutions finding. I dropped the v1 write-up from news because its displayed date (2026-07-09) appears reset and the benchmark predates the window. I added two items the draft missed: The Information's coverage, and the public MSA (Proximal AI, Inc., updated 2026-07-06), whose default terms keep IP with Proximal and give the customer a non-exclusive licence. Founders: all three are confirmed through the Scribble announcement and the v2 author list. Only Justus Mattern has a verifiable headshot (a single-person photo on his own site, HTTP 200). Calvin Chen and Navid Pour have none, and their prior-exit and Cursor-title claims remain uncorroborated. Web search was exhausted partway through and Bing results were unreliable, so a broader press sweep was limited. I found no evidence of acquisitions, partnerships or named customers.

Related vendors

Sources

www.proximal.ai/ · 2026-10-05, Homepage. Card reads 'Announcing our Seed Fundraise and Revenue Milestones'. FrontierSWE v2 card reads '34 tasks, 13 frontier models, 20-hour budgets'. No customer logos.
www.proximal.ai/blog · 2026-10-05, Blog index: FrontierSWE v2, Robustly Evaluating Cyber Capabilities, New Frontiers, FrontierSWE, Our Problems, Announcing Proximal. No dates shown on the index.
www.proximal.ai/blog/new-frontiers/ · 2026-10-05, 2026-09-29 funding post: $15M at a $300M valuation, General Catalyst lead, other investors, $200M annualized revenue claim, expansion areas, team backgrounds.
www.theinformation.com/newsletters/ai-agenda/general-catalyst-backs-codi · 2026-10-05, The Information (Stephanie Palazzolo): General Catalyst backs Proximal as it reaches a revenue milestone. Paywalled; only the headline and author were verified.
www.proximal.ai/blog/cybergym-cyberrl/ · 2026-10-05, 2026-09-30 CyberGym audit by Anish Lakkapragada, with CyberGym-Verified results.
www.frontierswe.com/blog/v2 · 2026-10-05, FrontierSWE v2 release post (September 2026): 34 tasks, Proximus harness, hardening, results table, core-team authors.
www.frontierswe.com/ · 2026-10-05, Live FrontierSWE v2 leaderboard (GPT-6 Astra 65.5%, Claude Opus 5.5 62.3%, Gemini 4 Argon 55.0%, among others).
www.proximal.ai/blog/frontierswe/ · 2026-10-05, FrontierSWE v1 write-up (shows 2026-07-09): 17 tasks, core team, 26 contributors, results.
www.proximal.ai/blog/proximal/ · 2026-10-05, Announcing Proximal; now shows 2026-06-23. No investors named.
www.proximal.ai/msa/ · 2026-10-05, Master Development Services Agreement, last updated 2026-07-06. Entity Proximal AI, Inc. Covers IP ownership and licence terms. No SOC 2.
github.com/Proximal-Labs · 2026-10-05, GitHub org: frontier-swe (231 stars), frontier-swe-v2 (37 stars), px-eval (1 star). No licences.
github.com/Proximal-Labs/frontier-swe-v2 · 2026-10-05, v2 repo: Harbor task layout, digest-pinned images, 'provided for evaluation purposes'.
github.com/Proximal-Labs/px-eval · 2026-10-05, Harbor task runner on Modal; 1 commit, last updated 2026-09-19.
www.proximal.ai/careers · 2026-10-05, 5 open roles: 3 in San Francisco, 2 in Bangalore.
www.proximal.ai/security/ · 2026-10-05, 404 (/trust/ also 404). No trust page.
www.justusmattern.com/ · 2026-10-05, Justus Mattern bio and headshot (/me.png, a single-person photo, image/png, HTTP 200). Links to x.com/MatternJustus.
www.calvinjaychen.com/ · 2026-10-05, Calvin Chen site: Proximal description and angel affiliations (now including Renaissance Technologies). No headshot.
www.linkedin.com/posts/imstusmith_excited-to-finally-share-that-scribble · 2026-10-05, Scribble Ventures announcement naming founders Calvin Chen, Justus Mattern and Navid Pour.
www.proximal.ai/blog/proximal · 2026-06-07, Announcing Proximal post, dated 2026-02-18; mission; team backgrounds (Cursor, Prime Intellect, Jane Street); fuzzy verifiers; reward hacking
www.proximal.ai/blog/our-problems · 2026-06-07, Open problems: fuzzy verifiers, reward-hacking detection, long-horizon RL environments, GitHub PR indexing, taskrunner framework, multi-node snapshotting
www.linkedin.com/company/proximalhq · 2026-06-07, Public snippet: 11-50 employees (~25 mentioned); Software Development; research lab for coding data
www.linkedin.com/posts/justus-mattern-a04230184_incredibly-excited-to-in · 2026-06-07, Co-founder announcement; data engine across domains
www.frontierswe.com · 2026-06-07, FrontierSWE benchmark; leaderboard of frontier models; implementation/research/performance tasks
github.com/Proximal-Labs/frontier-swe · 2026-06-07, FrontierSWE repo; 127 stars; ~400 commits; ultra long-horizon coding agent benchmark; license not shown
www.proximal.ai/security · 2026-06-07, Returned 404 - no public security/trust page found
www.crunchbase.com/organization/proximal · 2026-06-07, 403 Forbidden - not accessible

Last updated 2026-10-05 · Every quantitative field carries a source and a confidence tag. Fields we could not source publicly are marked unknown, never estimated. See the methodology.