Reinforcement Learning from Human Feedback

RLHF is the leading approach for aligning AI with human values.

By training your reward model with human judgments, you guide your system toward behaviors that feel natural, relevant, and aligned with the expectations of real users.

High‑quality preference data can be hard to source at scale. AI teams often struggle to recruit qualified evaluators, keep annotation quality consistent, and integrate feedback loops without slowing development.

Prolific enables you to collect high-quality preference data with verified specialists across any domain, task, or language.

Instantly source diverse evaluators. Ensure data quality with our robust verification. Integrate directly into your pipeline through our flexible API and get the data you need in hours, not weeks.