Our vision & method · LifecoreML
We’re building an artificial population with the depth, diversity, and continuity to bring more perspectives into the decisions that shape our world.
The ambition starts with a simple conviction: to understand a reaction, you need to understand the life behind it.
Explore the methodThe ambition
Imagine developing a product with a population you can return to. Exploring a new market through individual lives. Following an idea from its first sketch through the questions, compromises, and changes that make it useful.
That is the direction of Antestrata: a living research environment where a wider range of perspectives can inform everyday work.
People make decisions inside a wider reality: a place, a household, an economy, a culture. LifecoreML uses real-world distributions to ground the population in that context.
We are working toward a richer digital world twin, with the diversity and connections needed to explore how the same idea lands across very different lives.
A respondent has a connected biography: education, work, relationships, turning points, memories, habits, and priorities. Their circumstances belong together, so a preference has a history and a choice has a context.
The goal is depth that keeps revealing something useful when you look closer: the tension between what someone values, what they can afford, and what their responsibilities ask of them.
The population comes before the study. Your research criteria select individuals whose existing lives fit the audience you want to understand. Those individual histories are established before your audience criteria enter the picture.
We want teams to explore perspectives that rarely make it into the same room: different places, life stages, capabilities, obligations, and ways of seeing the world.
A page, pitch, price, or product meets a particular life. Relevant memories and priorities shape what stands out, what feels useful, what creates doubt, and how the respondent expresses a reaction.
We are building toward richer encounters with products and services, where attention, sequence, choices, and changing context become part of the research.
Persistent identity makes it possible to return to the same respondents. A revised concept can be explored with a familiar panel, and differences between people stay visible across the work.
Our ambition is research that accumulates understanding: panels that accompany a product through its development, with memory and context that make the next question more useful.
The engine inside Antestrata
LifecoreML builds the individual lives that make this approach possible. The language layer gives each respondent a readable voice, drawing on an identity and context established before the study.
Our design principle is to make the connection understandable: the circumstances, memories, and experiences that matter to a reaction should help you make sense of it.
The people are newly synthesized. Real-world distributions inform the world they inhabit; each individual has their own created biography.
Explore artificial respondentsBuild with more perspective
A founding pilot brings this approach to your page, pitch, product, or pricing. Meet the perspectives that could change your next version.
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