NEW RESEARCH REPORT
The 10 essential questions to ask before selecting a data annotation provider
The 10 essential questions to ask before selecting a data annotation provider
Download the free checklist & RFP guide to secure quality, safety, and scale
Your checklist to choose a vendor you can trust
Every provider promises “high quality.” Few can prove it—across security, scale, SME coverage, diversity, and ethics. The 10 Essential Questions gives you a ready-to-use framework to vet vendors and set measurable SLAs and KPIs.
Choosing a data annotation provider is a high-impact decision — especially for regulated, high-stakes, or complex gen AI programs. This whitepaper separates leaders from laggards across quality, security, scalability, ethics, and domain expertise metrics. You’ll get clear criteria, red flags to watch for, and RFP prompts you can copy-paste.
50% of companies buy/lease gen AI models from external vendors
Inside the report...
Practical guidance to de-risk vendor selection and set the bar for performance:
- Crowdsourcing vs. curated teams: Why anonymous crowd labor harms quality and privacy — what rigorous sourcing and training look like.
- Vetting, training, and QA: Skills tests for gen AI tasks (summarization, paraphrase, creative writing), multi-pass review, and live guideline updates.
- Subject-matter experts on demand: When (and how) to staff medical, legal, financial, and technical SMEs.
- Enterprise-grade security: What to require (ISO 27001, SOC 2 Type II, GDPR/CPRA, HIPAA/PCI where relevant) and how to verify.
- Track record & scale: Evidence of delivery since 2008+, referenceable enterprise wins, and rapid ramp without quality drop-off.
- Secure facilities: Clean-room operations, access controls, monitoring, and residency options.
- Bias & diversity: Why geographically diverse teams matter; cultural context training to reduce bias.
- Strategic consulting: Beyond throughput—guidelines, measurement, drift detection, and workflow design.
- Ethical standards: Fair pay, safe conditions, and processes that produce fair, privacy-preserving labels.
- RFP toolkit: Copy-ready questions, “leader vs. laggard” scorecards, and acceptance KPIs.
Your model is only as good as the people behind the
labels.
Certification isn’t a logo — it’s a recurring audit and an
operating discipline.
