The Expert Workforce for AI.
Credential-verified professionals create training data, evaluate models, establish ground truth and red-team frontier AI — with consensus built in.
Ground truth from real attorneys — not crowds.
Generic labeling farms optimize for volume. We optimize for judgment: licensed professionals, paid fairly, measured on agreement — so your model learns from people who actually do the work.
Seven bounty primitives. One quality engine.
Every task routes to matched experts, aggregates through multi-expert consensus, and escalates disagreements to senior adjudicators.
Grade model outputs against professional standards.
Author gold-standard prompts, answers and rationales.
Work real problems end-to-end so models learn how.
Pairwise preference judgments with written reasoning.
Adjudicate disagreements and certify ground truth.
Record expert tool-use traces for agents.
Find failures, jailbreaks and unsafe advice.
Live bounties
View marketplace →Judge LLM answers on Delaware M&A indemnification clauses
Stress-test a claims-triage agent with adversarial FNOL reports
Write gold-standard incident response playbooks (ransomware)
Why teams switch from crowd labeling.
| Crowd platforms | ExpertAIData | |
|---|---|---|
| Workforce | Anonymous clickworkers | License-verified professionals |
| Quality | Single-pass labels | 3–5× consensus + adjudication |
| Auditability | No provenance | Row-level audit trail |
| Outcome | You QA the noise | We certify the output |
From scope to certified dataset in five steps.
Define the task, rubric and acceptance criteria with our solutions team.
Credential-gated routing pairs work with verified experts in hours.
Redundant experts label blind; disagreements escalate to adjudicators.
Every row ships with provenance, agreement scores and audit logs.
JSONL, Parquet or direct API streaming into your training stack.
License lookups, ID checks, and domain assessments gate every expert. Only credentialed professionals see regulated work.
3–5× redundant labeling with Expert Score weighting, Cohen's κ tracking and blind senior adjudication.
Export JSONL, Parquet or pipe directly to your training stack via API. Full provenance on every row.
Teams shipping safer models say it best.
“ExpertAIData cut our legal-eval hallucination rate by 41% in one quarter. The consensus layer is the product.”
“We replaced three annotation vendors. The audit trail alone made our compliance team sign off in days.”
“Finally, red-teamers who actually hold the licenses our regulators ask about.”
Every profession that matters.
Train AI. Get paid.
Red-team challenges pay up to $5,000 per verified failure. Your expertise is the exploit.
Questions, answered.
How are experts verified?+
License and board lookups, government ID checks, and a domain assessment per specialty. Regulated work is only visible to experts with matching credentials on file.
What does consensus actually mean?+
Every task is completed blind by 3–5 matched experts. Agreement is measured with Cohen's κ; low-agreement items route to senior adjudicators before delivery.
How fast can we get data?+
Most programs see first certified batches within 48 hours of scoping. Enterprise SLAs guarantee throughput commitments in writing.
How do experts get paid?+
Per accepted task, with quality bonuses tied to Expert Score. Payouts run weekly via Stripe Connect in 40+ countries.
Build the dataset your model deserves.
Scope a pilot in one call. First certified batch in 48 hours.