Real-world data
for AI.
RL environments and expert human data to train frontier models and evaluate agents.
Our Partners
What we build
RL environments and expert human data, in the domains where public datasets run thin.
RL environments
Step one: build the environment
We stand up a sandboxed copy of the real system: the tools, the starting state, and a bank of tasks written by people who do the work.
- Environment
- invoice-reconciliation
- Tasks
- 180
- Built by
- Finance-ops specialists
Illustrative examples. Environment specs available on request.
- ✓SandboxInbox · ERP · spreadsheet
- ✓Seed state1,200 invoices, POs and receipts
- ✓Task bank180 tasks from real AP tickets
- ✓Verifiers3 state checks + expert rubric
How it works
From first call to signed offer in four steps. We handle the matching and the back-and-forth.
- 01
Intro call
A quick intro call to understand what you have: the domain, the data or expertise, and what you want out of it.
Live00:12YouIntro call · DataSynchrs
- 02
Matched with a partner
We introduce you to the right partner from our network: Mistral AI, Hugging Face, Surge AI, Handshake AI, Scale AI and more.
Partner network
Match
- 03
Valuation with the lab
You meet the lab directly. They review a sample and value your data on quality, rarity and volume.
Lab review · sample
Quality0.86Rarity0.72Volume0.58✓Valuation ready
- 04
Sign the offer
Terms arrive in writing. Sign the offer and we stay with you through delivery.
Offer
Signed