Rainscreen facade contractor · United States

AI takeoff for facade estimating

Reads the architectural drawings, counts the panels, and prices the job, inside the estimating workflow the team already used.

Shipped
  • Next.js
  • Supabase
  • Claude
  • pdf.js
  • Bluebeam round-trip
Architecture: drawing extraction, estimator verification, and the correction learning loop

The problem

Facade takeoff is manual measurement from PDF elevations. It is slow, it is the estimator’s whole day, and a missed opening or a curved wall measured off the elevation turns into a real loss on the job.

What we built

  • Vector-first takeoff that extracts panel geometry directly from drawing PDFs
  • Overlay viewer to verify, correct, or delete every extracted region
  • Cost engine driven by attributes (perforated, curved, fire-rated, custom colour) matched to $/sqft, $/lf, and $/ea rates
  • Bluebeam round-trip: export to CSV, correct in Revu, re-import, reprice
  • Openings deducted properly; curved walls measured from plan, never from the projected elevation

What the AI does

The takeoff itself is AI-assisted extraction from construction documents, plus a scope brief that reads across sheets. The part that matters commercially is the learning loop: every correction an estimator makes is stored and retrieved as a few-shot example on later runs, so the system converges on that specific estimator’s judgement instead of a generic model’s.

A note on numbers

We do not publish performance metrics we cannot substantiate, and we do not publish client results without the client's agreement. If you want to talk to a reference about a specific engagement, ask and we will arrange it where the client is willing.

Try it free for
three months.

We build one working AI integration into the business you already run, at our cost. You use it free for up to three months. No contract, cancel anytime, and you only pay if you keep it.