Simulationcompany reported
Physical AI Simulation
Simulation and model-development work for physical AI and robotics.
Commercial
Official websiteSimulatorCatalog available · 1
Genesis AI
Physics simulation engine and foundation model for robotics
Genesis AI builds a universal robotics foundation model trained on synthetic data from its proprietary physics simulation engine, which generates high-fidelity training data up to 430,000x faster than real time. It emerged from stealth in July 2025 with a $105M seed round co-led by Eclipse Ventures and Khosla Ventures, and unveiled its GENE model line in 2026.
Backers include Eric Schmidt and Bpifrance; open-sourced the Genesis physics simulator
This legacy directory profile is awaiting claim-level source migration. Existing values are retained, not upgraded to verified facts.
| Website | genesis-ai.company |
|---|---|
| Domains | Robotics, Simulation, Machine Learning |
| Location | San Francisco, Paris |
| Team size | 26-50 |
| Founded | 2024 |
| Funding | Seed, $105M (Eclipse Ventures, Khosla Ventures, July 2025) |
| Founders | Zhou Xian, Théophile Gervet |
Capability coverage
Focus areas and technical capabilities are shown separately. Missing technical evidence remains Unknown.
Catalog-evidenced technical capabilities
Unknown. No source-backed catalog capability record is available yet.
Capability catalog
Products and services supported by official company materials. Reviewed 2026-08-16.
Environments & datasets
Verified public artifacts and documented private commercial inventory.
No verified catalog items recorded yet. This does not mean the company has no environments or datasets.
Sources
Structured sources have not yet been migrated for this profile.
Improve this record
Company representatives and researchers can propose sourced changes. Submissions do not directly overwrite editorial data.
Similar startups
Also listed under Robotics, Simulation, 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 |