Company
Teaching machines the physical world.
Aurora is an early-stage company building synthetic data and simulation infrastructure for Physical AI. Our long-term goal is direct: become the cloud for simulating the physical world — the place where robots, vehicles, and vision systems gain experience before they ever touch reality.
Principles
Infrastructure, not demos
Synthetic data only matters when it is programmable, repeatable, and scalable. We build the boring, load-bearing parts first.
Ground truth is the product
Pixels are cheap. Perfectly labeled pixels, at distribution scale, under controlled variation — that is what moves models.
Failures are data
The most valuable training scenarios are the ones a model currently gets wrong. The loop from failure to dataset should be measured in hours.
Simulation earns trust through transfer
A synthetic frame is only as good as the real-world performance it produces. We optimize for transfer, not for pretty renders.