● Grounded in real census data — not made-up personas

Poll the world without contacting a soul.

Ask any question to a representative synthetic audience built from real public population data. Get a simulated response distribution in minutes — and, unlike anyone else, an honest calibration score that tells you exactly how far to trust it.

Every digital respondent is drawn from real age, sex, education and income structure. No panels. No wait. No guessing in the dark.

Question: “How likely would you be to try a new oat-milk energy drink in a 250ml can?”  ·  US adults 25–44, n=600
Very likely
31%
Somewhat likely
38%
Not sure
12%
Somewhat unlikely
11%
Very unlikely
8%
Calibration: back-tested against a real benchmark poll — predicted shares within 4.8pp of ground truth. Reliable for direction & ranking.
How it works

Real people become the data. The model just answers for them.

We don’t invent personas. We sample real, weighted respondent profiles from public microdata, condition a language model on each one, and aggregate the answers the way a real survey would.

01

Real grounding

Personas drawn from US Census microdata and World Bank population structure — real age, sex, education and income, weighted to the population.

02

Simulate

A language model is conditioned on each individual respondent and answers your question in character — single choice, 1–5 scale or open text.

03

Aggregate & calibrate

Weighted distribution, segment breakdowns, margin of error — plus a back-test against real data so you know the accuracy on your topic.

Why this one is different

The only synthetic-audience tool that shows its own accuracy.

Synthetic respondents are a powerful shortcut — but they’re a model, not a mirror. Everyone else asks you to take it on faith. We measure the gap for you.

Feed in a real labelled poll and calibrate mode simulates every real respondent, then reports how closely the prediction matches reality — mean error, total variation, per segment. You launch knowing whether this is a confident read or a loose hypothesis.

What people use it for

A fast first read, before you spend on a real study.

Message & concept testing

Pre-screen taglines, product concepts, packaging and naming across segments in minutes.

Pricing & positioning

See how willingness and preference shift by age, income and market before you commit.

Opinion & attitude reads

Directional reads on how different populations lean — with explicit confidence, not false precision.

Survey design

Dry-run a questionnaire, spot dead questions and sharpen options before you field for real.

The honest part

We’ll tell you when not to trust it.

Simulated responses are directional. They can under-represent minority and extreme views. For high-stakes calls, calibrate first and validate with real fielding. We build that caution into every report — because a number you can trust beats a number that sounds confident.

Early access

Be first to poll a whole population in a coffee break.

The web app is in private beta. Grab early access, or run the engine today on Apify.