Design studies with AI, collect responses from matched participants, and generate analysis grounded in real data — not model hallucinations.
How it works
A complete research pipeline — design, collect, analyze, and act — powered by AI agents and real respondent data.
01
Describe your goal. An AI interview agent builds your study design — method, population, sampling, and sample size.
02
Generate survey questions, set eligibility rules, share via link or QR, and gather responses from matched participants.
03
Run live analysis while collection is open, then generate a final report — every finding backed by real response data.
Built for everyone
Researchers, respondents, field collectors, and organizations — all connected through a shared credits economy.
Design studies with AI, publish surveys, monitor insights in real time, and generate grounded reports.
Browse eligible surveys, earn credits for quality responses, climb status tiers, and spin bonus raffles.
Take on field (CAPI) or remote collection jobs. AI matching ensures you're the right fit for every assignment.
Shared workspace for research teams — collective projects, member roles, and one team wallet.
One account can hold multiple roles — switch anytime from your sidebar.
Platform capabilities
Adaptive interview that turns your research goal into a rigorous study design.
Directional findings while collection is still open — spot trends early.
Ask follow-up questions grounded in your findings only. No outside speculation.
AI matches respondents and collectors to studies with 85%+ profile fit.
Six verification levels unlock premium surveys and higher incentives.
Public or private surveys with shareable links and QR codes.
One transparent wallet for AI agents, incentives, and earnings.
Audio, video, ratings, and open text — plus CAPI field collection with GPS.
Analysis draws exclusively from cleaned responses for the specific survey version — never from external data or model knowledge. Every finding cites the exact response IDs that support it. Uncited findings are rejected before saving.
// finding validation
✓ finding accepted
claim: "Majority prefer mobile over branch"
evidence: [r_042, r_089, r_103, r_117]
confidence: high · n=156
✗ finding rejected
reason: no verifiable response citations
Join researchers, respondents, and teams building collective intelligence on Qollectiv.