What we set out to build
To give small operators AI bookkeeping help without their financial records leaving their control.
What was built
- A local-first architecture with a static-export front end
- A white-list launch model rather than an open signup
- Waitlist and environment configuration built for a staged rollout
What it achieves
- Financial data stays on the user's machine by design, which is a claim the architecture supports rather than a promise in a privacy policy
The stack
Next.js, TypeScript.
Common questions
How was this built?
This was built through Colabs, our sister company. A founder brought the idea and the domain knowledge, Colabs brought the team, the founder funded the build with a monthly subscription, and they hold equity in the company that resulted. We label every case study, because a studio that publishes its prices and argues the other side of its own comparisons has to be equally precise about its own portfolio.
What state is it in?
Pre-launch. We state that plainly rather than describing everything as production: several things here are deliberately gated, and the reason is usually evidence rather than a missing feature.
Can you build something like this for us?
That is the point of publishing it. The same patterns are in the catalogue at published prices, and you can scope your own version on the plain-English page without contacting us first.
Where to next
If something here is close to what you need, the same patterns are in the catalogue at published prices, or you can describe your version in plain English and get it scoped and priced without talking to anyone.