Note2Quote
Site notes become professional quotes: a deliberately low-code build that shipped fast for tradespeople.
The question I was chasing
When is the right move not to build it from scratch?
I build native apps and SaaS from the ground up. The test here was the opposite instinct: a tradesperson needs a working tool that turns rough site notes into a clean quote, and they need it now, not after a six-week build. Could low-code get something genuinely useful into their hands faster than custom code would?
Why it exists
Tradespeople lose real money in the gap between doing the work and writing the quote: notes on a phone, a job half-described, an estimate that eats an evening to type up. The job is to turn what you jotted on site into something you can send a customer in minutes.
The constraints
Speed to a working product was the whole point, so hand-rolling a stack would have been the wrong instinct. It had to take messy, multimodal input (notes, the way a tradesperson actually captures a job) and hand back something that reads as professional. And it had to be simple enough to use one-handed on a site, not a CRM that needs onboarding.
The decisions that mattered
Go low-code on purpose (Pickaxe for the AI product layer and Framer for the front, with Claude doing the language work) because the fastest path to a useful tool was assembling proven pieces, not writing them.
Keep the surface area tiny: notes in, quote out. The discipline was resisting every feature that would have turned a sharp utility into another piece of trade software nobody finishes setting up.
What it is
A low-code AI tool that turns site notes into professional quotes instantly, with multimodal input, built for tradespeople who need fast, accurate estimates without the hassle.
Built with: Pickaxe, Framer, Claude
Where it landed
Live, and a useful reminder to myself that the builder's job is choosing the right tool, not always the hardest one. Low-code got a real product in front of users quickly. If demand pulls it that way, the natural next step is graduating the parts that need more control into custom code, while keeping the low-code speed everywhere it's still winning.
Part of the Rolling Waves work archive.