Register with structure
Capture expertise, demographics, device fit, and availability through guided contributor registration.
Keep intake, screening, assignments, and study history connected from the first record forward.
Capture expertise, demographics, device fit, and availability through guided contributor registration.
Use screener logic, human review, eligibility tags, and internal notes before participants are routed into paid or high-sensitivity work.
Assign, track, review, and close research work without letting operational context drift apart.
Support reusable participant networks with clearer fit, memory, and invitation control.
Build reusable contributor systems that keep qualification signals, study history, and invitation context visible across future programs.
Operate broad programs for surveys, interviews, concept testing, and product feedback without losing participant context over time.
Support healthcare, policy, technical, financial, or industry-specific contributors with higher trust and qualification requirements.
Build repeat-ready networks for model evaluations, annotation programs, red-teaming, feedback missions, and ongoing reviewer panels.
Build research programs from contributors connected to universities, health systems, and globally recognized knowledge networks.
University of Cambridge
Cambridge
UCL
University College London
University of Edinburgh
Edinburgh
ResearchAI serves both contributors and research operators with distinct paths, clearer permissions, and a cleaner starting point for every program.
Create a contributor profile, share your background, and be considered for relevant studies, expert reviews, interviews, and evaluation programs.
Participant SignupReview applicants, manage cohorts, route study work, and keep research operations governed from one secure environment.
Researcher LoginKeep invitations, notes, progress, and payout readiness inside the same operating flow.
Move from recruitment to completion with clearer operational visibility across cohorts, active work, and closeout states.
Bilingual reviewer network
Decision-maker panel
Clinical specialists
Repeat contributor cohort
Review quality, coverage, and study readiness without patching together separate tools.
Identify weaknesses in geography, language, devices, expertise, or availability before they create recruitment bottlenecks.
Use reviewer notes, prior outcomes, and completion history to improve study matching and contributor selection over time.
Build repeat-ready contributor networks instead of losing context after each interview cycle, task batch, or evaluation round.
A curated view of AI research stories from leading UK schools and universities, with direct links to the original university sources.
Embed review gates, participant protections, and operational discipline directly into the platform.
Use internal review steps, fit scoring, and study-specific approval criteria before live work begins.
Preserve participation history, trust notes, and repeat-cohort status across the network.
Keep screening, notes, eligibility, and program readiness tied to the same record.