Real-world data for physical AI
A decade of robots in the wild. Now we tell you which data is worth training on.
More than 30% of robot data never makes it into a model. Formant grades every take at capture against your spec, so you train on verified hours, not raw footage.
WHAT IT CAPTURES
Real-World Experience, Graded and Formatted for Physical AI
Not piles of clips. A continuous, verified pipeline, with provenance on every take.
Synchronized Telemetry & Egocentric Vision
First-person stereo video, synced frame by frame with joint dynamics, torque, IMU and operator intent. Embodied data, captured the way the robot experienced it.
Every Take Graded Against Your Spec
Hand pose, 3D bounding, task execution and visibility are checked at capture. Every take is marked Accepted, Needs Review or Not Accepted, with the reason. Failure data comes back labeled, not lost.
Cut, Named, and Formatted to Your Spec
Tasks arrive as structured records, with every step segmented and labeled. Bring an existing dataset and we'll enrich it, grade it and format it to your model's requirements.
BUILT FOR BOTH SIDES OF THE DATA MARKET
Audited, Not Assumed.
Model Builders, Labs & OEMs
Audit Before You Buy
A robot dataset can cost $1M. Know what's usable before you sign. Get verified egocentric datasets with provenance, hand-pose overlays and 3D ground truth, and target new collection at the gaps your model actually has.
Data Collectors & Suppliers
Prove Your Data Is Worth Buying
Buyers will ask if your hours are usable. Answer with a verifiable, take-by-take quality report instead of a sample reel. Start with a free data audit.
SEE IT IN PRACTICE
Egocentric Stereo Data, Graded at Capture.
Dual-eye egocentric streams from human and robot task runs add dense 3D spatial data to standard telemetry. Every frame is graded before it reaches your training set.
The Data Verification Loop
Capture → Grade → Label → Deliver → Recollect where the gaps are.
How it works
Is Your Data Worth Training On?
Stop buying unverified raw video. Whether you're buying a dataset or selling one, find out what's usable before the deal.