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Scopeout for learning

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.

Product model · updated today
Segments6 · mobile iOS weakest
What works herefewer fields, express pay
What did notprogress bars, badges
Backed by38 runs · confidence shown per claim
Used by every operator
Yours, exportable

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.

Seeded on day one · from what exists
Code · 3 repos
Docs · Notion, 412 pages
Tickets · 18 months
Past experiments · 22
First hypothesesfrom your evidence

Updated by every loop

Each research brief, interview, test and rollout writes back what it learned, with confidence.

Updated by run #118
Learnedsaved addresses lift mobile iOS most
Confidence3 runs · rising
Segmentmobile iOS · weakest step
Written byTest · Improve

Used by every operator

Research cites it, Design draws from it, Test sets expectations with it, the roadmap ranks by it.

Used by every operator
Research cites it
Design draws from it
Test sets expectations with it
The roadmap ranks by it

Built for compounding

Address step conversion · by segment
Desktop92%
Mobile · Android74%
Mobile · iOS46%
Tablet80%
Weakestmobile iOS · the model targets it first

Segments that matter

Which users behave differently and where, learned from your data rather than assumed.

Patterns that worked here · confidence
Fewer form fields5 runs
Express pay above fold3 runs
Guest checkout first2 runs
Trust badgeslost twice

Patterns that worked

Fewer fields, express pay, guest checkout: what moved the number on your product, not in a blog post.

Claim · “fewer fields lift mobile”
Backed by5 runs · +2.1% avg
Last confirmedrun #118 · Sep
Contradictednever
Editableyes · edits recorded

Confidence, not certainty

Every claim in the model shows how many runs back it and when it was last confirmed.

Run #118 · export
Notion
Confluence
PDF
links stay live

Yours, exportable

The model is your data. Export it, inspect it, correct it.

Start from a prompt.

Ask

“What do we know about why mobile iOS users abandon checkout?”

Run this when my batch opens →
Ask

“Which patterns have won on our pricing page, and how confident are we?”

Run this when my batch opens →
Plan

“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 waitlist

Private beta. We onboard teams in small batches. Or contact us.