Minds

Minds creates reusable synthetic audiences from a brief, file or link and runs message tests, concept comparisons, pricing probes and structured studies against them in minutes. Minds PRISM source modelling underpins the simulations, with per-persona profiles and results traceable to individual responses.

Minds builds synthetic audiences that stand in for real target groups during research. A user supplies a brief, a file or a link, and the platform identifies the audience dimensions that matter for the question at hand, then assembles a reusable panel of simulated respondents with an explicit profile for each individual Mind. Segment allocation is set precisely, so a study can mirror the weighting of a real population rather than a loose approximation of one. The product covers a wide range of research jobs. A team can test a single message, compare competing concepts, probe pricing reactions, or run a fully structured study with the same underlying audience. Simple questions are quick to set up, while decisions that need more rigor expose more control over how the study is framed. Results remain traceable back to the individual responses and the reasoning behind them, which matters when a synthetic finding has to survive scrutiny from stakeholders. Beneath the surface, Minds PRISM source modelling anchors the simulations. The site cites audience examples such as U.S. Gen Z (7,983 data points), European fast food consumers (7,426 data points) and global health care workers (6,871 data points), which signals how granular the underlying panels can get. Customers shown on the homepage span consumer brands, agencies, research institutes and publishers, and there are dedicated entry points for brands, agencies and research partners. Minds sits in an unusual spot in the AI tool landscape. It is not a chatbot that answers questions and not a survey fielding service; it is closer to a simulation layer that sits in front of a research question. That makes it a fit for marketing and product teams that need directional insight in minutes, and for research organizations that want to test hypotheses before committing budget to fieldwork. Teams expecting it to replace statistically validated primary research outright should read the published validation work first.