build your audience
Bring your first-party data.
We model your customers across 150+ attributes per agent, built from real data and real behaviour, segmented by behavior, market, and decision triggers. Build it once and it's there for every study after, no rebuild.
What you can run against it
One model. Five kinds of study.
Agentic CX Simulation
Simulate customer journeys with AI agents modeled on your audience to see how experiences perform before launch.

Attention Heatmaps
Drop a campaign into a simulated network and watch opinion move. Useful when the risk isn't whether people like it but whether one segment reacts loudly.

Focus Groups
Explore a topic with a simulated audience and uncover the reasoning behind each response.

Surveys
Ask a focused question at scale. Compare responses across segments and see the pattern behind the choice.

Creative Alignment & Optimisation
Compare creative against your audience to identify the strongest direction and refine it before launch.

Agentic CX Simulation
Simulate customer journeys with AI agents modeled on your audience to see how experiences perform before launch.

Attention Heatmaps
Drop a campaign into a simulated network and watch opinion move. Useful when the risk isn't whether people like it but whether one segment reacts loudly.
Focus Groups
Explore a topic with a simulated audience and uncover the reasoning behind each response.
Surveys
Ask a focused question at scale. Compare responses across segments and see the pattern behind the choice.
Creative Alignment & Optimisation
Compare creative against your audience to identify the strongest direction and refine it before launch.
Frequently asked questions
The questions buyers ask.
Is this a general-purpose LLM with prompts on top?
Does our data train your model or leave our tenant?
How do you validate accuracy, and against what?
What if we build this internally?
Is this a general-purpose LLM with prompts on top?
Does our data train your model or leave our tenant?
How do you validate accuracy, and against what?
What if we build this internally?
Is this a general-purpose LLM with prompts on top?
Does our data train your model or leave our tenant?
How do you validate accuracy, and against what?
What if we build this internally?
Rehearse The Future
Australia
Level 3, 102 Victoria St, Carlton VIC 3053 Australia
1 Denison St Level 16, North Sydney, NSW 2060, Australia
United States
95 Third Street, 2nd Floor, San Francisco, CA 94103
© 2026 Socialtrait. All rights reserved.
Rehearse The Future
Australia
Level 3, 102 Victoria St, Carlton VIC 3053 Australia
1 Denison St Level 16, North Sydney, NSW 2060, Australia
United States
95 Third Street, 2nd Floor, San Francisco, CA 94103
© 2026 Socialtrait. All rights reserved.


