The human world is the training set. We capture high-fidelity human motion and interaction in the real world — and turn it into robot-ready data.
Full-body · Hands · Ego
6-DoF trajectories
Unconstrained, in the wild
Three Stanford graduates
Physical intelligence is bottlenecked by data, not architecture. Robot learning needs enormous quantities of high-quality real-world interaction — captured with human dexterity, at human scale, in unconstrained environments.
Scraped, cheap, effectively unlimited.
Teleoperation is slow, costly and lab-bound.
Every hand, every day — currently uncaptured.