Prolific

Overview

Prolific is a purpose-built platform for collecting high-quality, real human data at scale. Designed for both AI development and academic research, it connects researchers with a large, diverse pool of verified participants who complete tasks, surveys, and evaluations quickly. The platform emphasizes speed and reliability, enabling researchers to obtain human insights in minutes rather than weeks, while maintaining strict data quality standards. With a focus on representativeness and ethical compensation, Prolific has become a trusted infrastructure for organizations that need defensible, human-sourced data.

For AI teams, Prolific provides essential human feedback for preference tuning, safety evaluations, and benchmark construction. The platform supports representative population sampling, ensuring that the data collected reflects a wide range of demographics and perspectives—critical for building robust and defensible AI systems. Features such as Audience Finder allow fine-grained targeting, while built-in quality controls help screen responses, reduce noise, and ensure that the resulting dataset is trustworthy. Prolific's Human Feedback API further enables direct integration into AI development pipelines, making it a flexible tool for iterative model improvement.

Beyond AI, Prolific accelerates research across disciplines. Academic institutions and industry labs use the platform to recruit participants for behavioral studies, market research, product testing, and more. The platform is trusted by thousands of organizations, including leading AI/ML developers and universities. It has been used to power large-scale studies on environmental decision-making, AI governance, and state-of-the-art multimodal model development, demonstrating its versatility and impact. Participants are verified for reliability, and transparent payout mechanisms ensure a steady supply of engaged contributors.

Prolific also offers an ecosystem for developers and researchers who need deeper integration and advanced evaluation methodologies. The HUMAINE framework and Leaderboard provide structured approaches to understanding human preferences in LLMs, while Agentic Evals and Benchmarks support testing autonomous agents. Domain Experts, such as coding developers, are accessible for specialized evaluation tasks. Managed services, a citations library, and comprehensive help centers complete the offering, supporting projects from small academic studies to enterprise-scale data collection with equal rigor.

Core capabilities

Representative Human Feedback

Access diverse, verified participants for preference tuning, safety evals, and benchmarks that are defensible.

Audience Finder

Target specific demographics, behavioral traits, and screening criteria to build representative study samples.

Data Quality Tools

Built-in attention checks, screening mechanisms, and participant verification ensure high-quality responses.

Human Feedback API

Programmatically integrate Prolific's participant pool into AI development workflows for continuous feedback loops.

Agentic Evals & Benchmarks

Run human evaluations on agentic systems using structured tasks and validated metrics.

HUMAINE Leaderboard

Compare LLM performance using a human-preference evaluation framework designed for more meaningful benchmarks.

Domain Experts

Coding Developers: Recruit specialized programming experts for code-related evaluations, user studies, and research.

Managed Services

Let Prolific handle participant recruitment, scheduling, and study management for complex or large-scale projects.

Use cases

Preference tuning for large language models

Safety evaluations and red-teaming of AI systems

Building standardized benchmarks for model comparison

Academic research requiring diverse human subjects

Market and product research with targeted demographics

AI governance and democratic policy-making with public input

Multimodal AI development requiring fast, high-quality human annotation