It learns your product. Every run.
A living model of your product, your users by segment, and what has worked for whom. Every research brief, test and rollout updates it, so the next call starts smarter.
The thing an autonomous team accumulates
Humans forget, rotate and leave. The product model keeps what the product has learned about itself.
Built from what already exists
Code, docs, tickets, analytics and past experiments seed the model before the first prompt.
Updated by every loop
Each research brief, interview, test and rollout writes back what it learned, with confidence.
Used by every operator
Research cites it, Design draws from it, Test sets expectations with it, the roadmap ranks by it.
Built for compounding
Segments that matter
Which users behave differently and where, learned from your data rather than assumed.
Patterns that worked
Fewer fields, express pay, guest checkout: what moved the number on your product, not in a blog post.
Confidence, not certainty
Every claim in the model shows how many runs back it and when it was last confirmed.
Yours, exportable
The model is your data. Export it, inspect it, correct it.
Start from a prompt.
“Which patterns have won on our pricing page, and how confident are we?”
Run this when my batch opens →“Propose three tests for onboarding based on what has worked for new teams.”
Run this when my batch opens →Questions, answered.
Is the model trained on our data?
It is built from your data and stays yours. It is not used to train models for other customers.
Can we correct it?
Yes. Every claim is editable and every edit is recorded.
What happens on day one?
It reads what exists: code, docs, tickets, analytics, past tests. The first hypotheses come from your evidence.
Stop running the business. Start directing it.
Join the waitlistPrivate beta. We onboard teams in small batches. Or contact us.