
Prolific is a human data collection platform that provides fast access to verified participants, AI taskers, and domain experts for research studies and AI training, evaluation, and safety workflows via self-serve tools, integrations, and managed services.
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ProlificProlific is a technology company that connects AI developers, researchers, and product teams with real people to quickly collect high-quality, human-derived data online. The company positions itself as creating the biggest pool of high-quality human-derived data in the world, offering an “ultimate platform” to access it for uses ranging from behavioral research to AI training, evaluation, and safety testing. The platform emphasizes participant verification, fair pay, and rigorous data-quality controls to reduce fraud, bots, and low-effort responses. Prolific highlights its internal multi-layer quality system (“Protocol”), which combines identity checks, ongoing fraud detection, in-study authenticity checks, and performance-based controls to maintain reliable results. Prolific supports both self-serve usage (pay-as-you-go) and expert-led managed services for teams needing end-to-end execution. It also provides integrations via simple links and an API to connect common research/annotation tools or custom systems. The company states it was co-founded at Oxford University in 2014 and has been trusted for 10 years by AI developers, academics, and organizations. It describes itself as a remote-first, fast-scaling business backed by $32M in Series A funding (secured in 2023).
HC score
verified business cases

Pre-qualified specialist taskers trained in evaluation protocols for complex AI training and evaluation tasks (e.g., benchmarking, factuality checking, side-by-side comparisons).
Trained Evaluators
Evaluation Protocols
Audience Filters
Tool to search and match qualified audiences (global crowd, domain experts, AI taskers) and view the number of matching participants for specific criteria.
Audience matching
Domain Experts
AI Taskers
Access to verified subject matter experts and qualified professionals (e.g., STEM, healthcare, programming, PhDs) for domain-specific AI training, validation, and research, via platform or managed services.
Verified Experts
Credentials Verification
Audience Filters
A public benchmark and evaluation framework for assessing model behavior in real-world, human-facing conditions, developed through peer-reviewed research and ongoing empirical work.
Public Benchmark
Evaluation Framework
Human-centered Testing
No-code (link-based) and API integrations with common research and data collection tools; includes partner integrations such as Maze and Gorilla and supports custom tools.
No-code links
API integrations
Custom tools
Expert-led, end-to-end data collection with dedicated quality assurance and project execution for AI or complex research, including sourcing, training/onboarding, multi-stage QA, and reporting.
Complete Datasets
Expert Curation
Custom Sourcing
Self-serve access to Prolific’s verified participant network to launch studies/tasks quickly with audience filters, screening, messaging, workspaces, and integrations via link or API.
200k+ Participants
300+ Filters
Custom Screening
API-level integration to automate and scale human data workflows, connecting Prolific participants to custom-built tools and internal systems for tasks, data collection, and evaluation pipelines.
API integrations
Workflow automation
System integration

University of New Mexico
Researchers at the University of New Mexico needed to run a complex longitudinal study over 30 days and maintain participant engagement. They faced the challenge of executing repeated surveys across the full study period. They needed a way to keep participants involved throughout the longitudinal timeline. The research team used a platform to recruit participants and manage participation across repeated surveys. They implemented a setup that supported sending and administering surveys multiple times over the 30-day period. They relied on the platform to help coordinate ongoing participation across the study. The study achieved a 90% survey completion rate across the full 30-day period. Participant engagement was maintained through the end of the longitudinal study. The research effort successfully collected repeated survey responses over the entire 30-day timeline.
Skills
Project Details
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