AI Benchmark Research
Independent research and public benchmark analysis on AI capabilities.
Nonprofit research institute behind FrontierMath and AI capability benchmarks
Epoch AI is a nonprofit research institute that studies AI trends and builds rigorous benchmarks, including FrontierMath and the Epoch Capabilities Index. Not a startup selling environments, but a key independent evals organization; Mechanize's founders previously led Epoch.
FrontierMath benchmark commissioned by OpenAI
This legacy directory profile is awaiting claim-level source migration. Existing values are retained, not upgraded to verified facts.
| Website | epoch.ai |
|---|---|
| Domains | Math, Machine Learning |
| Location | Remote |
| Team size | 11-25 |
| Founded | 2022 |
| Funding | Philanthropic grants (nonprofit) |
| Founders | Jaime Sevilla, Tamay Besiroglu @tamaybes |
Focus areas and technical capabilities are shown separately. Missing technical evidence remains Unknown.
Unknown. No source-backed catalog capability record is available yet.
Products and services supported by official company materials. Reviewed 2026-08-16.
Independent research and public benchmark analysis on AI capabilities.
Verified public artifacts and documented private commercial inventory.
Structured sources have not yet been migrated for this profile.
Company representatives and researchers can propose sourced changes. Submissions do not directly overwrite editorial data.
Also listed under Math, Machine Learning.
| Name | Domains | Type / catalog | Location | Team | Funding | Raising |
|---|---|---|---|---|---|---|
| Rise Data Labs RL environments and tasks across multiple domains, supported by a large expert network | Computer Use, Coding, Finance, Cybersecurity, Legal, Data Labeling, Enterprise, Multi-Domain, RLHF, Custom Environments | Data + environments 3 artifacts | New York, United States | 11-25 | - | Unknown |
| Applied Compute Ex-OpenAI trio applying RL to build specialist enterprise models | Enterprise, Machine Learning, Custom Environments | Pure-play commercial Catalog unknown | San Francisco | 11-25 | $80M total at $700M valuation (Oct 2025) | Yes |
| Artificial Analysis Independent benchmarking of AI models across intelligence, speed, and price | Multi-Domain, Machine Learning | Pure-play commercial Catalog unknown | San Francisco | 11-25 | $2.6M (2024) | Unknown |
| Bespoke Labs Data curation and RL environment recipes from ex-Google DeepMind researchers | Coding, Machine Learning | Pure-play commercial Catalog unknown | Mountain View, Menlo Park, Bangalore, San Francisco | 11-25 | ~$40M (reported) | Unknown |
| Collinear Enterprise simulation, judges, and long-horizon trajectory generation | Enterprise, Long Horizon, Machine Learning, Simulation | Pure-play commercial Catalog unknown | Mountain View, Sunnyvale | 11-25 | - | Unknown |
| Diffuse Labs ML and long-horizon RL environments | Machine Learning, Long Horizon | Pure-play commercial Catalog unknown | Palo Alto, San Francisco | 1-10 | - | Unknown |