Machine Learning
Environments where agents do machine learning itself: reproducing papers, debugging training runs, tuning models, and improving benchmark scores under compute budgets. These are among the hardest long-horizon environments, and the most strategically interesting, since they measure a model's ability to improve models.
18 companies · 0 cataloged artifacts · as of 2026-08-16
| Name | Domains | Type / catalog | Location | Team | Funding | Raising |
|---|---|---|---|---|---|---|
| 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 |
| EdotEnv Long-horizon planning environments for frontier models | Long Horizon, Machine Learning | Pure-play commercial Catalog unknown | San Francisco | 1-10 | - | Unknown |
| Epoch AI Nonprofit research institute behind FrontierMath and AI capability benchmarks | Math, Machine Learning | Pure-play commercial Catalog unknown | Remote | 11-25 | Philanthropic grants (nonprofit) | Unknown |
| General Reasoning Open reasoning data and reward models from the ex-Meta AI reasoning lead | Finance, Long Horizon, Machine Learning | Pure-play commercial Catalog unknown | London, San Francisco | 1-10 | ~$10.9M (reported) | Unknown |
| Genesis AI Physics simulation engine and foundation model for robotics | Robotics, Simulation, Machine Learning | Simulator Catalog unknown | San Francisco, Paris | 26-50 | Seed, $105M (Eclipse Ventures, Khosla Ventures, July 2025) | Unknown |
| LMArena Crowdsourced model leaderboards from the Chatbot Arena team | Multi-Domain, Machine Learning | Pure-play commercial Catalog unknown | San Francisco, Berkeley | 26-50 | $100M seed (a16z, UC Investments, 2025); $150M at $1.7B valuation (Jan 2026) | Unknown |
| Nous Research Open AI lab behind the Atropos RL environments framework | Machine Learning, Environment Platforms | Environment platform Catalog unknown | New York | 11-25 | Series A, $50M led by Paradigm (~$1B valuation, 2025) | Unknown |
| Osmosis Forward-deployed reinforcement learning for AI agents | Machine Learning | Pure-play commercial Catalog unknown | San Francisco | 1-10 | Seed, $7M (CRV, Audacious Ventures, YC) | Unknown |
| Preference Model Stealth startup working on preference and reward modeling | Machine Learning, Coding | Pure-play commercial Catalog unknown | San Francisco, Toronto, Seattle | 11-25 | - | Unknown |
| Prime Intellect Open superintelligence stack: compute, RL environments hub, and sandboxes | Machine Learning, Environment Platforms, Multi-Domain | Environment platform Catalog unknown | San Francisco | 26-50 | Series A, $130M at $1B valuation (2026); $150M+ total | Unknown |
| Scaled Foundations GRID: a simulation-first platform for robot learning | Robotics, Simulation, Machine Learning | Simulator Catalog unknown | Seattle | 1-10 | - | Unknown |
| Snorkel Programmatic data platform expanding into expert evals and RL environments | Multi-Domain, Coding, Machine Learning, Data Labeling, RLHF | Data + environments Catalog unknown | San Francisco, Redwood City, New York | 101-250 | Series D, $100M at $1.3B valuation (2025) | Unknown |
| SynthLabs Post-training research: synthetic data and scalable RL alignment | Machine Learning, Alignment, RLHF | Data + environments Catalog unknown | San Francisco | 1-10 | Seed (M12 and First Spark Ventures, 2024) | Unknown |
| Vmax Converts proprietary data into RL environments | Machine Learning, Custom Environments | Pure-play commercial Catalog unknown | San Francisco, New York | 1-10 | - | Unknown |
Available environments, datasets & benchmarks
Source-backed catalog records connected to machine learning.
No verified artifact records in this domain yet. This is a coverage gap, not evidence that no artifacts exist.