


Train robots on physics-accurate simulation environments.
Physicl provides the sim-ready environments, physics-tagged assets, and scene variations your training loop needs — for manipulation, navigation, and long-horizon tasks.
The data infrastructure layer for robotics simulation.
Physicl generates, normalizes, and validates the physics-accurate 3D environments and assets your simulator needs — from raw inputs to training-ready output.
Normalization
Raw inputs converted to structured, physics-tagged, sim-ready 3D.
Augmentation
Infinite scene variation through controlled domain randomization.
Sim-ready export
Physics-accurate assets and environments, direct to your simulator.
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Human-validated, every step.
10,000+ 3D specialists and physics reviewers verify geometry, materials, and physics properties before any asset ships.
500k+ sim-ready objects and millions of variations.
Highly detailed 3D spaces designed for full-scene simulation.




API and Engine Integrations
Drop sim-ready assets directly into your existing pipeline. Native compatibility with Isaac Sim, MuJoCo, Unreal, Omniverse, and Unity — via Python SDK or REST API.

Why Physicl





Built with physics, not just visuals
Every asset ships with collision meshes, mass, friction, and articulation data — derived from geometry, not manually estimated.
Millions of assets in production
100,000+ sim-ready assets generated per month, across thousands of categories — scaling with your training pipeline, not against it.




10,000+ experts review every asset
3D specialists and physics reviewers verify geometry, materials, and sim-readiness before anything ships. 98% QC pass rate.
Export-ready for your tools
USD outputs — direct to Isaac Sim, MuJoCo, Unreal, or Omniverse. No conversion, no cleanup.







Affordances, materials, relationships, physics
Every asset includes articulation range, material properties, object relationships, and physics tags — structured for training, not just rendering.
Get the training data your robots need.
Used by leading robotics and AI labs. Request beta access or talk to the team.






