Expected Parrot
Research with humans and AI, in one platform.
Expected Parrot is an open-source, model-agnostic platform for designing studies, running them with AI respondents, fielding them to real people, and comparing results across humans, models, and methods. It addresses the cost and iteration time of traditional user research and social science by pairing AI simulation with validation against real respondents in a single workflow.
Core capabilities include a survey builder for surveys, experiments, interviews, screeners, scales, and labeling workflows; AI personas created from real data or synthetic traits; an AI interviewer for adaptive, AI-moderated interviews; human panels for fielding to real respondents; side-by-side comparison across personas, segments, models, and human samples; analysis tools for summarizing, theming, and classifying responses; and custom deliverables such as reports, briefs, datasets, and slide-ready outputs. The platform is Python-friendly with an edsl package, GitHub resources, documentation, and notebooks.
It serves universities, research labs, startups, nonprofits, and enterprises. For researchers, there is a free account with pay-as-you-go credits, the option to use your own API keys, and credits earned through referrals. Enterprise teams can contact the company for shared workspaces, shared credits and usage controls, dedicated support, and custom integrations and tooling.
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