You can buy training data. You can’t prove it’s good.
Data for physical AI is bought as an input. We’re building the market where it’s bought as a result.
Nobody can check what data they bought
A compute receipt proves a process ran. A delivery proves files moved. Neither proves that hands stayed in frame through the moment of contact, that a demo shows the task it’s labelled with, or that a clip has the permissions your use needs.
Those are the things that decide whether data is usable, and the hardest to check. A file can parse fine and be worthless. A label can look right and be wrong. You find out weeks later, in a training run that underperforms for reasons nobody can trace.
A market for results
A market for results
Today you buy an input and take on the risk yourself. We think you should buy a defined result and get the proof with it. There are three things make that work.
How it works
Each market covers one kind of processing: video quality, audio transcription, annotation, fraud detection, privacy removal. A market sets its own unit of work, formats, quality policy and verification rules. Identity, settlement and the checking rails are shared, so launching a market takes configuration instead of new engineering.
Operators claim jobs, run the pipeline against the published spec, and submit signed results. Validators re-check a sample and vote. Payment follows acceptance.
The spec is published before collection starts, so most quality questions have one right answer. Resolution, stability, framing, whether faces were removed: any validator gets the same result. Tolerances have stated limits. Judgment calls, like describing what someone is doing in a clip, go to several validators who have to agree. Known-answer tasks run through the queue throughout, so anyone submitting without doing the work gets caught.
How it works
Each market covers one kind of processing: video quality, audio transcription, annotation, fraud detection, privacy removal. A market sets its own unit of work, formats, quality policy and verification rules. Identity, settlement and the checking rails are shared, so launching a market takes configuration instead of new engineering.
Operators claim jobs, run the pipeline against the published spec, and submit signed results. Validators re-check a sample and vote. Payment follows acceptance.
The spec is published before collection starts, so most quality questions have one right answer. Resolution, stability, framing, whether faces were removed: any validator gets the same result. Tolerances have stated limits. Judgment calls, like describing what someone is doing in a clip, go to several validators who have to agree. Known-answer tasks run through the queue throughout, so anyone submitting without doing the work gets caught.
Follow the build
We publish as we build. Engineering progress, processing results, and new participants as they join.