OpenMatterOpenMatter

Train robots on the world they’ll actually see.

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Simulation for the full physical AI lifecycle

Rehearse

Your robot runs the job in physics long before it runs it on hardware.

Harvest

Every pass hands back labelled trajectories. Nothing collected by hand.

Score

Each checkpoint measured against the last, with the numbers behind it.

A run is one line, drawn four times.

  1. 01

    Upload

    URDF, the scene, your checkpoint.

  2. 02

    Simulate

    4,096 passes, varied every time.

  3. 03

    Fine-tune

    Trained on what came back.

  4. 04

    Ship

    Artifacts out. Our copy deleted.

We keep the compute. You keep everything else.

simulated812 GB
dataset48.3 GB
weights2.1 GB
eval report1.8 MB

Screened bar is discarded when the run closes.

50.4 GB delivered

Questions

Train on the world it will actually see.

We are taking on a small number of robots at a time. Tell us what yours has to do.

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