Crescia builds AI models of real individuals, each started from one person's own intake answers, so product teams can put a product decision to them and see which option each picks and the reason it gives, before they build.
Results are simulated: AI models built from real people's intake answers, not real customers.
A structured intake records one real person's own answers about how they shop and decide. From it, we build their twin.
Group twins into a panel. We tell you how many twins are on it and how each was built.
Put a product choice or concept to the panel. Each twin returns a choice and a written reason.
Each twin starts from one real person's answers. Panels are built from individuals, not from population averages.
Every response comes with a written reason, so teams can read the stated reasoning as well as the choice. The reasons are generated text.
Twins supplement real research. We say what a result can support and what it cannot.
Crescia is built to accelerate user research.
Put a choice or concept to a panel early, while there is still time to change course.
Use it to decide which questions deserve a study with real customers.
Product, growth and research teams, and the agencies that support them.