The human intelligence layer for fast-moving AI teams
Why Prolific for human data in AI?
Efficiently managing human feedback gets tougher as AI teams scale. Prolific's infrastructure, designed to streamline human data collection, makes it easy to get quality data fast for all AI use cases.
Support all data requirements
Access a full spectrum of participant types through a single platform.
From specific evaluations to general feedback, Prolific supports all your research needs across different workstreams and project types.
Work based on what your project needs
Self-serve through our platform with pay-as-you-go pricing to launch projects instantly. No subscription fees or minimum commitments.
Need end-to-end support? Use our managed services for participant sourcing, quality management, and project execution—so your engineers can focus on model development.
FEATURES
Trusted by AI/ML developers, researchers, and leading organizations across industries.
Questions?
Traditional labeling providers use large annotation teams on hire. They offer little transparency into their profiles and selection criteria.
Prolific gives you direct access to verified evaluators through self-serve or managed options. This gives you both the quality assurance of managed services and the transparency and control of direct access, with much faster turnaround times.
Our infrastructure scales from simple pilot evaluations to enterprise-wide data collection programs. With access to 200k+ participants, our flexible API, and expert-led managed services, you can keep expanding the volume and complexity of your evaluations without having to rebuild your operational foundation.
Our API-first approach allows seamless integration with your development environment and evaluation systems. As a result, we support all types of data formats for training and evaluating AI models and products.
With Prolific's platform, you can run parallel evaluation programs across different teams and workstreams. Each project can have custom participant requirements, data needs, and timelines while sharing the same infrastructure. This removes bottlenecks and enables independent team operations without duplicating operational overhead.
