One of the first things people ask about Poll-Sim is: How accurate can AI really be when predicting how real people will react?
We took this seriously and built our system around three key principles:
Granular, real-world audience grouping You can simulate broad publics (e.g. Australian Public by generations or US population by age & eco-social class) or go hyper-local, like Victorians/Melbournians broken down by living/born locations.
Objective, detailed group descriptions with balanced coverage Every audience group comes with rich, neutral background info covering culture, values, political leanings, economic context, in-group variations, and more so the AI has solid context instead of guessing.
Real demographic percentages Groups are weighted by actual population data (for example, our Victorian major cities breakdown uses real proportions like 27% third-generation Anglo-Celtic, 24% established migrants, etc.). This ensures the overall simulated result reflects realistic audience composition rather than treating every subgroup equally.
The result? Much more grounded, believable simulations whether you're testing a speech, policy idea, product announcement, or controversial post.
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Creators. Consultants. Integrators. All are welcome.
We teamed up with @Vercel for a special launch day, which means there s a dedicated leaderboard full of teams shipping on Vercel, all in one place. More launches, more competition, more reasons to spend too long refreshing the page.
