The clearing layer for AI training data.
Anonymous, request-driven matching between AI labs and vetted data & RL-environment suppliers. No brokers. No identities. Just the match.
Three steps. Both sides stay blind until settlement.
Request
A lab posts an RFD: task, eval harness, budget, license, constraints. The request goes live; the lab's name and roadmap never do.
Match
Vetted suppliers are matched to the spec by capability, never by identity. Demand finds supply without either side exposed.
Settle
Every sample is scored against the lab's own eval. On match, the deal clears through escrow, and only then do identities reveal.
Source data you can't buy off a shelf.
- POST
- Define an RFD: task, eval, budget, license terms.
- STAY ANONYMOUS
- Suppliers see the spec, never your name or roadmap.
- VERIFY
- Every sample is scored against your eval before you pay.
- RL ENVIRONMENTS
- Commission custom environments, not just static sets.
Get matched to demand that already exists.
- GET VETTED
- One capability review, then you're a vetted supplier.
- SEE REQUESTS
- Browse anonymized requests by capability, never by who's asking.
- PROVE
- Submit against the eval; the protocol scores you objectively.
- CLEAR & GET PAID
- Settle on match, identity revealed only at clearing.
United Data takes no side, holds no inventory, brands no supplier. It is a protocol, not a broker, just the rails the trade clears on.
Anonymous
No identities until clearing. Demand can't leak; suppliers can't be poached around the protocol.
Neutral
No markup on either side, no owned supply we'd rather sell. We never compete with the people on our rails.
Verified
Every match is scored against the demand-side eval. Provenance, licensing and indemnity clear with the deal.