What AI Labs Actually Look For in Data Partners

The 6 Criteria That Matter

1. Domain Expertise Depth

Labs want annotators who actually understand the domain. A PhD annotating NLP data. A sysadmin designing terminal benchmarks.

2. Quality Infrastructure

Not just QC but a system — multi-tier pipeline, inter-annotator agreement, real-time dashboards.

3. Scale Without Quality Degradation

Can you go from 1,000 to 100,000 without quality dropping?

4. Turnaround Speed

AI cycles are measured in weeks. Pilot batches in days, not weeks.

5. Data Security

SOC 2, GDPR, data residency, audit trails — required for enterprise procurement.

6. Pilot Framework

500 examples, 5-day turnaround, automated reporting, clear pass/fail criteria.

What Does Not Matter (As Much)

• Price per label — quality at $5 beats garbage at $0.50
• Headcount — 100 experts beat 10,000 crowd workers

The data partners that win prove quality at scale. Everything else is secondary.