#10

Halluminate

Commercial

high confidence

www.halluminate.ai ↗ · Status: active confirmed · Founded 2024

Halluminate (YC S25, founded 2024, San Francisco) calls itself a data research lab building benchmarks and RL environments for knowledge work, starting with financial services (PE, IB, due diligence) and consulting. It raised a $30M Series A led by Oak HC/FT in October 2026 ($38.5M total). With about nine people, it says it works with four of the five leading closed-source US AI labs and has a mid-eight-figure revenue run rate (self-reported). Its flagship benchmark is Westworld Finance Diligence Bench.

Key facts

Headquarters

San Francisco, CA, USAconfirmed cite

Headcount band

1-10reported cite

Total raised

$38.5Mconfirmed cite

Last round

Series A, $30M, 2026-10-01, led by Oak HC/FTconfirmed cite

SOC 2

unknown

What they sell

mixedconfirmed cite

Open source

yesconfirmed cite

Deployment

managed-hosted (fully managed, parallelizable sandbox environments); also bespoke/custom environments for enterprise clientsconfirmed cite

What's new

6 sourced updates · last 6 months

1 Oct 2026funding Halluminate raises a $30M Series A led by Oak HC/FT; total funding now $38.5M
Sources are the company post and a Fortune exclusive. Oak HC/FT led, with YC, Orange Collective, FT Partners and Heavybit participating; Fortune and TechTimes add unnamed angel ML researchers from Anthropic, OpenAI and Meta. Fortune reports nine employees. The company says it went from $0 to a mid-eight-figure revenue run rate in 10 months and is 'strongly profitable' (self-reported). Per FinSMEs, the money goes to systems-engineering and AI-research hiring, compute, and financial simulation sandboxes.
Why it matters: A nine-person vendor now has $38.5M in funding and says it has a mid-eight-figure run rate. That makes it one of the better-funded vertical (finance) RL-environment vendors.
1 Oct 2026customer Company says four of the five leading closed-source US AI labs are customers (self-claimed, none named)
The Series A post says Halluminate has 'built and scaled RL environments with four of the five leading closed-source U.S. AI labs'. Fortune and TechTimes repeat the claim and describe them as paying customers. No lab is named. TechTimes reports that the near-term priority is to go deeper with frontier-lab customers rather than expand to enterprise buyers.
Why it matters: This is a strong frontier-lab signal for program managers, but it is self-claimed and no customer is identified.
1 Oct 2026other CEO describes a 'Moore's law of environments'
Jerry Wu told Fortune that environment complexity has to roughly double every 6 to 8 months to stay useful for training frontier models.
Why it matters: It shows how the vendor plans its roadmap: long-horizon environments whose complexity keeps rising, not static task sets.
11 Aug 2026benchmark Westworld Finance Diligence Bench released
The benchmark has 88 problems covering the full due-diligence process for a company acquisition. They are built from anonymized real private-deal data and run in dynamic desktop environments. There are seven task categories: modeling 14, underwriting 13, quality of earnings 9, data preparation 11, pitch materials 15, closing 4 and diligence review 22. Eight models are scored on two harnesses (native CLI and CU+TU). On the current blog table the top mean score is 0.59 (Opus 5.5). Series A press (Fortune, TechTimes) cites 51% as the top score, likely from an earlier set of models. No public repo or leaderboard is linked.
Why it matters: This is the company's flagship finance benchmark and the core of its pitch to labs. It shows frontier models still score well below expert level on long-horizon diligence work.
27 Jul 2026research Sim-to-real transfer study for web agents (Goodbuy clone vs Best Buy)
Victoria Knapp Perez trained Qwen2.5-VL-7B-Instruct with SFT and then GRPO (binary reward) on simulated, real and mixed data. Mixed training worked best on both sites (39.1% sim / 23.4% real at the best GRPO checkpoint), and real-to-sim transfer was much stronger than sim-to-real. A W&B report, a Hugging Face dataset and models were released.
Why it matters: It is an open, reproducible data point on whether simulated web environments transfer to real sites, which is the core question for buyers of synthetic environments.
17 Jun 2026benchmark DealTrace Bench: staged evaluation of a real private-equity deal
The benchmark has five graded stages: extract, reconcile, forecast, market and recommend. Claude Opus 4.7, GPT-5.5 and Gemini 3.1 Pro were evaluated, and GPT-5.5 was strongest on both judge scores and deterministic accuracy. Forecast quality was the strongest predictor of recommendation quality (standardized coefficient 0.75). The research index dates it 2026-05-15; the post shows 2026-06-17. A public DealTrace GitHub repo exists but was empty on 2026-10-05.
Why it matters: It shows where frontier models break in finance workflows (forward-looking forecasting), which is where the vendor sells environments.

Founding team

Jerry Wu

Co-founder & CEO

Previously led product and research at Capital One Labs, where he launched one of the first AI agents in banking and co-authored three patents. Studied Computer Science and Economics at Cornell.

Profile ↗

Wyatt Marshall

Co-founder & CTO

Cornell Milstein Scholar. Twice an early data/software engineer, doing large-scale data engineering at two early-stage NYC startups. Co-author of Westworld Finance Diligence Bench.

Profile ↗

What practitioners should know

For researchers

The finance benchmarks (Westworld Finance Diligence Bench, DealTrace) are published only as write-ups with per-model scores. No public task set or leaderboard is linked, and the DealTrace GitHub repo was empty on 2026-10-05.
Westworld Finance Diligence Bench scores differ between the current blog table (top 0.59, Opus 5.5) and the Series A press (top 51%). Cite the blog table with its date, because the model set appears to have been updated.
The sim-to-real web-agent study (2026-07-27) is reproducible: the HF dataset victoria-kp/goodbuy-bestbuy-mirrored-tasks, HF models and a W&B report are public. Method: SFT then GRPO on Qwen2.5-VL-7B-Instruct.
Older open releases: WebBench (MIT; ~2,454 of ~5,750 tasks open-sourced), westworld (Apache-2.0, plus an HF dataset), browserbench (no license shown), noodle-flights (MIT).

For program managers

$30M Series A led by Oak HC/FT on 2026-10-01, bringing the total raised to $38.5M. Fortune reported nine employees at the announcement, while the YC profile still shows a team size of 5.
Self-claimed and unaudited: a mid-eight-figure annualized run rate reached in 10 months, 'strongly profitable', and work with 4 of the 5 leading closed-source US AI labs. No lab is named.
Stated near-term focus (TechTimes): go deeper with frontier-lab customers rather than sell to enterprises. The homepage says it is expanding from finance into consulting and adjacent verticals.
The YC jobs page lists 9 open roles, including MTS Research/Post-Training, MTS Platform Engineering, MTS Finance Researcher, Strategic Project Lead and Chief of Staff.

For data ops

Experts are supplied as 1099 finance contractors (PE, IB, consulting, accounting, FP&A) paid $100-$250/hour with a minimum of 20 hours a week for 6 weeks, per the company's Expert Network page.
The finance environments run as desktop sandboxes graded by deterministic checks plus rubric-based verifiers, per the company's benchmark write-up.
The GitHub org keeps forks of Harbor and harbor-cookbook (updated Aug 2026), which suggests familiarity with the Harbor eval/RL format. Official support is not stated.
No SOC 2, security page or trust center was found on halluminate.ai as of 2026-10-05.

Benchmarks & research

6 published

Westworld Finance Diligence Benchbenchmark · 11 Aug 2026

88 due-diligence problems for company acquisitions, built from anonymized real private-deal data and run in dynamic desktop environments. There are seven task categories (modeling, underwriting, quality of earnings, data preparation, pitch materials, closing, diligence review). Authors: Alina Hyk, Robert Alward, Victoria Knapp Perez, Wyatt Marshall. No public repo or leaderboard.

Current blog table: top mean score 0.59 (Opus 5.5, native CLI and CU+TU). Fable 5.1 scored 0.56/0.58 and GPT-6.1 Sol 0.54/0.55. Series A press cited a 51% top score, likely an earlier model set.

Open ↗

Simulated-to-Real Transfer for Web Agents (Goodbuy/Best Buy study)paper · 27 Jul 2026

Small-scale study by Victoria Knapp Perez that trains Qwen2.5-VL-7B-Instruct (SFT then GRPO) on a simulated Best Buy clone (Goodbuy) and on the real site. The dataset and models are on Hugging Face, with a W&B report.

Mixed sim+real training beat either alone (39.1% sim / 23.4% real). Real-to-sim transfer was much stronger than sim-to-real.

Open ↗Paper ↗

DealTrace Benchbenchmark · 17 Jun 2026

Staged evaluation of a real private-equity deal: extract, reconcile, forecast, market, recommend. The research index dates it 2026-05-15. The GitHub repo (github.com/Halluminate/DealTrace) was empty when checked on 2026-10-05.

GPT-5.5 was strongest of Claude Opus 4.7, GPT-5.5 and Gemini 3.1 Pro. Forecast quality dominates recommendation quality (standardized coefficient 0.75).

Open ↗

Westworld v1environment · 23 Nov 2025

Sandbox environments of realistic simulated websites for training and evaluating computer-use agents. The open-source repo is Apache-2.0 per GitHub, and an HF dataset (Halluminate/westworld) is available.

Open ↗Paper ↗

BrowserBenchbenchmark · 22 Nov 2025

Benchmark of browser-infrastructure stealth, measuring how bot detection distorts browser-agent evaluation. No license is shown on the repo.

Open ↗Paper ↗

Web Benchbenchmark · 30 May 2025

Browser-agent benchmark built with Skyvern. The blog describes a full set of ~5,750 tasks across 500+ websites, of which ~2,454 tasks across 452 sites were open-sourced (MIT).

Anthropic Computer Use was best fully automated at 66.0% of tasks; the best agent reached 46.6% on write-heavy tasks.

Open ↗Paper ↗

Products

RL environments and benchmarks for knowledge work / financial services (custom, for frontier labs) ↗

Custom simulated desktop and web environments with expert-written tasks and verifiers for training agents on finance and consulting workflows. Sold mainly to frontier labs (self-claimed: 4 of the 5 leading closed-source US labs).

Westworld Finance Diligence Bench ↗

Flagship long-horizon finance benchmark (88 due-diligence problems).launched 11 Aug 2026

Westworld (simulated websites) ↗

Open-source simulated-web sandbox environments for computer-use agents (Apache-2.0).launched 23 Nov 2025

Expert Network ↗

Paid network of finance professionals (PE, IB, consulting, accounting, FP&A) who work as 1099 contractors. They write problems and rubrics at $100-$250/hour, with at least 20 hours a week for 6+ weeks, fully remote. Launch date not stated.

Data Partnerships ↗

Program inviting companies to 'turn your company's data and workflows into a new revenue opportunity' by partnering with Halluminate. Launch date not stated.

noodle-flights ↗

Open-source flight-search app for benchmarking and training agents (MIT). Last updated 2026-10-02.

Scale & velocity

Current headcount

9 (as of 2026-10-01)reported cite

Headcount growth

unknown

Open roles

9 listed on the YC jobs page as of 2026-10-05 (incl. MTS Research/Post-Training, MTS Platform Engineering, MTS Finance Researcher, Strategic Project Lead, Chief of Staff)confirmed cite

Other locations

unknown

Distributed / remote

unknown

Research depth

Has researchers

yesconfirmed cite

Researcher count

unknown

Backgrounds

Jerry Wu (co-founder/CEO): ex-Capital One Labs (led product and research; 3 patents); Cornell CS & Economics, Wyatt Marshall (co-founder/CTO): Cornell Milstein Scholar; data engineering at two early-stage NYC startups, Team includes former founders, researchers, particle physicists, experts and engineers from Meta, Scale AI, Capital One Labs, McKinsey and Goldman Sachs (company statement)reported cite

Capital

Total raised

$38.5M (including $30M Series A, Oct 2026)confirmed cite

Last round

Series A, $30M, 2026-10-01, led by Oak HC/FTconfirmed cite

Investors

Oak HC/FT (Series A lead), Y Combinator (S25), Orange Collective, FT Partners, Heavybit, Unnamed angel ML researchers from Anthropic, OpenAI and Meta (press-reported), Antigravity Capital (baseline, portfolio-listed), Batch Ventures (baseline, aggregator-reported), Team Ignite Ventures (baseline, aggregator-reported), Transpose Platform Management (baseline, aggregator-reported)reported cite

Valuation

not disclosed cite

Revenue signals

Self-reported: grew from $0 to a mid-eight-figure annualized revenue run rate in the 10 months before Oct 2026, 'strongly profitable'reported cite

Date	Round	Amount	Led by
1 Oct 2026	Series A	$30M	Oak HC/FT	source ↗

Security & compliance

SOC 2

unknown

Other certifications

unknown

Security page

unknown

Product

What they sell

mixedconfirmed cite

Open source

yesconfirmed cite

License

Mixed: WebBench (MIT), westworld (Apache-2.0), noodle-flights (MIT), browserbench (no license shown); the 2026 finance benchmarks are not open-sourced (DealTrace repo empty)confirmed cite

Deployment model

managed-hosted (fully managed, parallelizable sandbox environments); also bespoke/custom environments for enterprise clientsconfirmed cite

Maturity

GAestimated cite

Notable customers

⚑Four of the five leading closed-source US AI labs (unnamed) self-claimed cite

Buyer analysis

Best fit: Frontier labs that need long-horizon, expert-authored finance and knowledge-work RL environments and benchmarks (due diligence, PE deal analysis, modeling) in realistic desktop sandboxes.

How we verified this

2026-10-05 refresh: I opened and checked every source the draft cited: the company Series A post, Fortune, TechTimes, FinSMEs, the three 2026 research posts, the research index, the Web Bench and Westworld posts, the Expert Network and Data Partnerships pages, the YC profile, the GitHub org and the DealTrace repo. Both founder photos were downloaded and inspected. The core facts hold: the $30M Series A led by Oak HC/FT, $38.5M total, nine employees, the self-claimed mid-eight-figure run rate and four of five frontier labs, and the founders and their titles. Five corrections were made. (1) The 'two largest browser agent companies' customer claim was dropped; it is not in the cited source. (2) Two news items with invented dates (Expert Network, Data Partnerships) and an undated hiring item were dropped. (3) The Web Bench 'contradiction' was rewritten, because the vendor states both the full and open-sourced task counts. (4) The press figure of 51% was added next to the blog's 0.59 top score. (5) The unverified QLoRA detail was removed and notable_investors was downgraded to reported. Wyatt Marshall's LinkedIn link was added. The web-search budget was exhausted, so I could not run a fresh broad search for missed items. Within the pages I fetched I found no acquisition, shutdown or named frontier-lab partnership, but I cannot rule out uncaptured press in the window.

Related vendors

Sources

www.halluminate.ai/ · 2026-10-05, Homepage: data research lab positioning, finance and consulting focus, no security/SOC 2 mention
www.halluminate.ai/blog/series-a · 2026-10-05, Official Series A post, 2026-10-01, by Jerry Wu: $30M, Oak HC/FT lead, YC/Orange Collective/FT Partners/Heavybit, $38.5M total, revenue and lab claims
fortune.com/2026/10/01/halluminate-raises-30-million-series-a-oakhc-ft/ · 2026-10-05, Fortune exclusive: 9 employees, angels from Anthropic/OpenAI/Meta, 'Moore's law of environments', 51% top benchmark score
www.techtimes.com/articles/328407/20261001/finance-ai-tops-out-51-due-di · 2026-10-05, Series A coverage: frontier-lab-first strategy, profitability, 51% benchmark figure
www.finsmes.com/2026/10/halluminate-raises-usd30m-in-series-a-funding.ht · 2026-10-05, Series A recap (dated 2026-10-05) with use of funds
www.halluminate.ai/blog/due-diligence-bench · 2026-10-05, Westworld Finance Diligence Bench, 2026-08-11: 88 problems, 7 categories, authors, 8-model score table
www.halluminate.ai/blog/dealtrace · 2026-10-05, DealTrace Bench post dated 2026-06-17
www.halluminate.ai/blog/sim-to-real-webagents · 2026-10-05, Sim-to-real web-agent study, 2026-07-27, with HF and W&B links
www.halluminate.ai/research · 2026-10-05, Research index with dates (DealTrace listed 2026-05-15)
www.halluminate.ai/blog/benchmark · 2026-10-05, Web Bench: ~5,750 tasks / 500+ sites in full; ~2,454 / 452 open-sourced with Skyvern; Anthropic CU 66.0%
www.halluminate.ai/blog/westworld · 2026-10-05, Westworld v1 post, 2025-11-23
www.halluminate.ai/experts · 2026-10-05, Expert Network: 1099 contractors, $100-$250/hour, 20+ hours a week for 6+ weeks
www.halluminate.ai/data-partnerships · 2026-10-05, Data Partnerships program page
www.ycombinator.com/companies/halluminate · 2026-10-05, YC profile: founders, titles, bios, headshots, LinkedIn/X links, 9 open jobs, team size 5
github.com/Halluminate · 2026-10-05, GitHub org: WebBench, browserbench, westworld, noodle-flights, sample_sft, Harbor forks, empty DealTrace repo
github.com/Halluminate/DealTrace · 2026-10-05, DealTrace repo, empty when checked
huggingface.co/datasets/victoria-kp/goodbuy-bestbuy-mirrored-tasks · 2026-10-05, Sim-to-real study dataset (linked from the company post)
news.ycombinator.com/item?id=44865290 · 2026-06-07, Launch HN: deterministic/offline sandboxes, RLVR, Westworld, human data services, ~20% customer improvement claim
getlatka.com/companies/halluminate.ai · 2026-06-07, Reported $1.3M ARR, 12 employees (2025-09-14), $4M valuation, claims $0 raised/bootstrapped, conflicts with YC/angel backing
www.orangecollective.vc/portfolio/halluminate · 2026-06-07, Orange Collective portfolio listing
antigravity.capital/portfolio/halluminate · 2026-06-07, Antigravity Capital portfolio listing
www.halluminate.ai/blog/browserbench · 2026-06-07, BrowserBench blog, Nov 22 2025; evaluates Browserbase, Steel, Hyperbrowser, Anchor Browser
www.paraform.com/company/halluminate/cmo0vioko000e0djsvyvu9n6m · 2026-06-07, Job listing: Founding Member of Technical Staff (Research/Post-Training)
www.linkedin.com/in/jerry-wu-7814b0100/ · 2026-06-07, Jerry Wu LinkedIn (public snippet), co-founder/CEO

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.