Mercor matches you with experts. AuraOne turns expert work into human training data your team can use: identity checked, rights clear, reviewer notes included, and delivery files handed back to you. Your data stays with your program, not a shared pool.
Your contributors and your data stay tied to your program. The failure mode that exposed a competitor's worker and customer data is not the model to copy.
Keep your current talent source. Move one expert workflow into AuraOne, bring labeled data you already have, and prove reviewed delivery before you expand.
Most teams cannot validate or trace where their training data came from: 78 percent cannot validate it, and 77 percent cannot trace its origin. A clear consent trail is the answer enforcement asks for.
A fair comparison starts with what the other vendor already does well. The question that decides the deal is what survives an audit, and who owns the model in the end.
Matches you with experts
Mercor is strong at what it does: finding hard-to-fill specialists fast and getting them into the work. When the first job is filling expert capacity, that is a real advantage.
Keeps the data record with you
The same experts, plus a data record. Every datapoint carries who made it, who reviewed it, and under what rights. The reviewed dataset stays portable to your workflow.
The first signs the move worked. Procurement, engineering, and your model-risk team all see the same review record.
You have the people. What you lack is a clear record of what they made, a launch check that knows what the reviewer decided, and a regression bank that catches the same failure next time.
A competitor lost four terabytes, including worker data, because identities were thin and data sat in one pool. Here, identity is checked on every datapoint, and customer programs stay separated.
Week one picks the workflow and imports labeled data you already have. Week two runs reviewed delivery with identity and approval chains. Week three exports a review-ready file your procurement and risk teams can read.
A match is people. We attach identity, review, and rights to the data those people make, then hand you the dataset and handoff file. Bring your hardest case. We'll show you how it gets reviewed.