Pressure-test product decisions before the real users.
Bring a landing page, feature concept, pricing page, onboarding flow, or message.
antestrata returns individual reactions from synthesized respondents with composed biographies, behavioural profiles, and traceable reasons behind each response.
This is what antestrata produces. Real reactions from synthesized respondents composed before you arrived, to real concepts that real teams brought to a panel. Each respondent has a composed biography of several thousand words and a memory graph behind every reaction. Click any of them to read more.
Not a survey.
Not a chatbot.
A respondent field composed before the question is asked.
antestrata does not ask a language model to roleplay your audience on demand. Respondents are composed before the research question appears, with biographies, behavioural profiles, memory structures, and traceable reasons behind their reactions.
The language model does not invent the respondent. It narrates from the respondent’s composed state.
How it works
Bring the decision.
Landing page, pricing page, feature concept, onboarding flow, positioning, message.
Run the panel.
The same stimulus is shown to synthesized respondents with different backgrounds, constraints, and reaction patterns.
Read the friction.
You receive individual reactions, objections, misunderstandings, emotional hesitations, and reasons behind each response.
Before the real users.
Real recruitment is the slowest, most expensive part of product research. antestrata is faster and cheaper. That is the buyer’s side of the trade. The methodology exists to make sure the shortcut is worth taking.
Four properties that make the shortcut work
Depth.
Every respondent has a composed biography, behavioural profile, and memory graph.
Provenance.
Every response is connected to the moments in the respondent’s biography that shaped it.
Diversity.
The panel spans cultures, life stages, professions, and ways of seeing the world that real recruitment misses.
Persistence.
The same respondent remembers what they saw and said across sessions.
A world at meaningful resolution.
antestrata’s standing pool is a deliberate scale model. We over-represent the segments real recruitment misses, diaspora populations, multilingual professionals, rare professional intersections, geographies that survey panels under-cover. The world we are building is not a statistical sample of humanity; it is a working population designed for research where real recruitment is hardest.
The model targets thirty thousand respondents at v1 (H1 2027), growing toward seventy-five to a hundred thousand over the following year. Beta opens with two hundred fully composed respondents, biographies, behavioural architectures, memory graphs. We extend on demand from validated distributions for segments the pool does not yet cover.
Founding research pilots, open now.
We are opening a small number of paid research pilots to founders, product teams, and research-conscious agencies who want to pressure-test real decisions early. You bring a landing page, a feature concept, a pricing page, an onboarding flow, or a messaging hypothesis. We run it through a panel of synthesized respondents and return reaction-quality responses you can read.
The pilot returns what you actually use: respondents reasoning out loud, the moments they resisted, what created trust, which real-user segments to validate with next.
Questions antestrata answers well.
What antestrata does not do.
A few things antestrata does not do, stated plainly.
antestrata respondents are not modeled on, sourced from, or imitating real individuals. They are composed from documented frameworks. No real person’s biography is reproduced; no real person’s identity is reconstructed.
The standing pool is small. Beta launches with two hundred respondents. Some segments are richly represented; others are sparse. We extend on demand where we can, and we are transparent about which queries return reliably and which do not.
Respondents have rich biographies but no current-events awareness. They do not know what is trending this week. They do not know your specific brand context unless you tell them.
antestrata does not replace longitudinal research with real customers. It is for the early-stage reasoning work: concept pressure, segment hypotheses, internal alignment, the conversations that happen before commitment, not instead of it.
Powered by LifecoreML.
antestrata is the research tool. LifecoreML is the engine that composes its respondents.
The engine produces respondents from documented frameworks before any research question is asked, characters, biographies, behavioural architectures, memory graphs, all composed deterministically. The language model narrates the composed state when you query, but it does not produce the respondents themselves. They were composed by LifecoreML before antestrata handed them to you.
stagesseed→computed biography→life-trajectory simulation→memory graph→freeze and voice narration.