Minds Alternative for an AI Persona Panel With a Published Method
Minds assembles self-service panels of AI personas and claims its own accuracy figure. Panelia calibrates its method on arXiv and displays a confidence interval on every result.
Assembling a panel of AI personas to observe how responses spread out is no longer an isolated idea: several platforms are moving in that direction, each with its own calibration method. Minds is one of them, and the approach looks close to Panelia's in places, which makes the comparison worth making rather than a footnote.
What Minds offers
Minds (getminds.ai) is a Berlin based synthetic market research platform, built around a proprietary model called Minds PRISM. The approach is self service: you assemble calibrated AI personas into "panels" of 10, 50, or 100 personas to observe how responses distribute. The platform targets marketing teams, agencies, product teams, and B2B insight needs, and presents itself as GDPR compliant ("GDPR-native").
Minds claims an accuracy figure of 80 to 95 percent, a number communicated by the company itself: useful as an indicator, but best read as a self reported figure rather than a result verified by an independent third party.
A similar spirit, a different method
In principle, Panelia and Minds share a common intuition: simulating a panel with calibrated AI personas rather than recruiting a human sample for every test. The difference plays out on two concrete points. First, Panelia's calibration method is published on arXiv (identifier 2510.08338), letting anyone examine it, rather than relying on an accuracy figure communicated without method detail. Second, every Panelia result displays a confidence interval calculated on the resulting distribution, not just an overall platform accuracy score.
Two panel sizes, a different order of magnitude
Where Minds offers tiers of 10, 50, or 100 personas per panel, Panelia surveys hundreds of synthetic respondents per test, with a distribution designed to cover a target market broader than a room of a few dozen profiles. The result takes the form of a purchase intent distribution on a Likert scale, accompanied by verbatims and an executive summary, not just a table of individual responses to interpret.
The cost and time of the decision
Describing a concept, price, or message takes a few minutes, and the result arrives in roughly 10 minutes, at a cost of around one euro per test. That lets you run several iterations within the same day, without trading off the number of personas surveyed against available budget.
A method to verify, not to take on faith
Whether with Minds, Panelia, or any other tool of this kind, a synthetic panel remains a decision support tool, not a guarantee of a result identical to a human test. The question worth asking any provider of this type of service, Panelia included, is simple: is the calibration method verifiable, and does the result display a margin of error or a single figure presented as definitive. That is often where the difference lies between a tool you can challenge and one you simply have to trust.
Frequently asked questions
- Do Minds and Panelia use the same method?
- Both simulate a panel with AI personas, but Panelia's calibration method is published on arXiv and every result displays a calculated confidence interval.
- Where does Minds' 80 to 95 percent accuracy figure come from?
- It is a figure communicated by Minds itself, best read as a self reported number rather than an independently verified result.
- How many personas does Panelia survey per test?
- Hundreds of synthetic respondents, distributed according to the target market profile, versus tiers of 10 to 100 personas at Minds.