Human Evaluation as Recurring AI Infrastructure
Jemma White, COO of Prolific, on why humans ensure AI safety
This signals that human data demand is moving downstream from frontier labs into everyday AI software companies. These buyers are not just training base models. They are testing whether an AI product works for German support teams, Japanese consumers, or regulated enterprise users. That makes Prolific’s long built participant graph, with 40 plus countries, 80 plus languages, and detailed screening filters, a product advantage rather than just a marketplace asset.
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For an AI B2B company, language capability usually means post training and evaluation, not raw pretraining. A team might upload support replies, legal drafts, or sales chat outputs into AI Task Builder, route them to qualified raters by language or background, and get fast judgments on accuracy, tone, cultural fit, and safety.
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This is a different demand curve from the expert heavy frontier lab market. Handshake, Mercor, and Office Hours are strongest where tasks need PhDs or narrow domain credentials. Prolific is strongest where teams need broad but controlled human variation, across markets, demographics, and product contexts, to see how an AI system lands with real users.
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The workflow is also becoming more software like. Prolific launched AI Task Builder in December 2024, rolled out AI Taskers in March 2025, and joined Google Cloud Marketplace in December 2024. That lets enterprise AI teams buy and run human evaluation inside existing procurement and model development flows instead of through slow managed service projects.
The next step is that AI B2B companies will treat human evaluation like recurring infrastructure, not occasional research. As more models are customized for specific industries and geographies, the winning vendors will be the ones that can supply fast, auditable, globally distributed human judgment at product cadence, and that is exactly where Prolific is pushing its platform.