End-to-end evaluation and training data. Managed for you

From evaluator specification to data delivery - with the reproducibility and transparency your research demands. Hours to first data. Days to completion.

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Explore HUMAINE

200,000+ verified participants | 38+ countries | 300+ prescreening attributes

What we specialize in

Safety and red-teaming

Diverse, adversarial evaluator populations designed to find what benchmarks miss. Bias detection, edge-case discovery, and structured stress-testing.

Training and alignment

Verified domain experts delivering supervised fine-tuning, preference data, and alignment feedback. Recruited, trained, and quality-assured against your standards.

Evaluator specification

200,000+ verified participants. 300+ prescreening attributes. Domain expertise from PhD-level specialists to native speakers of low-resource languages. Define your evaluator cohort by demographics, expertise, language, and domain knowledge - then reproduce that exact population across experiments and model versions. We handle sourcing, verification, and training. You get evaluator populations that don't exist anywhere else with this level of specification.

Research-grade QA built into every project

Your dedicated team designs calibration tasks against your standards, runs multi-stage quality reviews, and monitors in real time. Every data delivery meets the methodological bar you'd set for a published study. Not just reliable data - auditable, reportable, publishable data.

Persistent infrastructure. Not one-off projects.

Most human evaluation is disposable: recruit, collect, discard, repeat. We build persistent evaluator infrastructure - pools that retain calibration, accumulate domain knowledge, and scale on demand without starting over.

How fast-moving AI teams use Prolific

Trusted by AI/ML developers, researchers, and leading organizations across industries

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Unpacking human preference for LLMs - The HUMAINE framework

The evaluation of large language models faces significant challenges. Technical benchmarks often lack real-world relevance, while existing human preference evaluations suffer from unrepresentative sampling, superficial assessment depth, and single-metric reductionism.

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Building breakthrough AI faster

Ai2 reduced human data collection from weeks to hours with Prolific, building state-of-the-art multimodal AI models faster without sacrificing quality.

Persuasion by AI

The paper shows that certain prompting and post-training methods dramatically increase LLM persuasiveness on political issues — but at the cost of factual accuracy.

Gemini 3 Pro: Frontier safety framework

The frontier safety framework report for Google’s latest model.

Prolific for AI managed service questions

Can I specify my evaluator demographics?

Yes. 300+ prescreening attributes including age, gender, ethnicity, education, first language, country of residence, professional domain expertise, and more. You define the evaluator population; we assemble and verify it.

How do you verify evaluator identity and quality?

Every participant is identity-verified. Projects include calibration tasks designed with your team, attention checks, multi-stage QA review, and real-time quality monitoring by your dedicated quality lead.

Can I report your methodology in my methods section?

Yes. We provide full methodological transparency - evaluator demographics, recruitment criteria, quality assurance procedures, and task design documentation - in a format designed for inclusion in academic methods sections.

How does managed services work?

We begin by understanding your needs through a requirements workshop, collaborating on task design to meet your goals. Our team handles participant sourcing, tool setup, and calibration tasks to ensure quality standards. Depending on the project type and complexity, you’ll start receiving datasets in weeks, with continuous optimization based on your feedback.

Close the gap between your models and your evaluations.

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Explore HUMAINE