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How to extract quantities from blueprints automatically

A practical walkthrough from PDF sheet set to counts, lengths, and areas - in the Kamai app or through the API - with every number traceable to its sheet.

To extract quantities from blueprints automatically, let a model that understands construction drawings do the reading: upload the PDF sheet set, let foundational models identify the rooms, walls, and fixtures, review what they found, and export the quantities. With Kamai that loop - upload to export - takes minutes, and every number stays traceable to the sheet it came from.

Step 1: Upload the sheet set

Start with the PDF set you already have. Vector PDFs exported from CAD are the ideal input because they carry the original geometry; the models read that geometry directly rather than a picture of it. Multi-sheet, multi-trade sets are the normal case: upload the set, not a hand-picked page.

Step 2: Review what the models found

Processing runs in minutes per sheet set. What comes back is not a highlighted PDF but layers of structured findings over your drawing: areas (room boundaries, plan footprints), lines (wall centerlines, perimeters), and objects (doors, windows, fixtures), each with its measurement.

Review is where automated takeoff earns trust. Click any quantity and you land on the geometry that produced it, on the sheet it came from. You confirm by looking, not by re-measuring - which is what makes the review pass fast enough to keep the speed you gained.

Step 3: Export the quantities

Once the takeoff reads true, export the structured quantities into your estimating workflow. Kamai's job ends at quantities on purpose: your cost data, production rates, and bid strategy live in your estimating tool, and a takeoff layer should feed that tool rather than replace it.

Doing the same with code

Everything above is also an API. The flow is three calls - upload the PDF, poll the job, fetch a GeoJSON FeatureCollection of classified geometry - and it slots into pipelines where no one opens a drawing at all. The takeoff API guide has the complete walkthrough with working Python.

Why traceability matters

Automated extraction is only useful if you can stand behind the numbers in a bid. The property to insist on - in Kamai or any tool - is that each quantity links back to its source geometry. Provenance turns "the AI said 4,200 square feet" into "sheet A-102, this boundary, 4,200 square feet", and that is the difference between a demo and a number you bid with.

Common questions

Areas (plan footprints, gross and net room areas), lengths (wall centerlines, perimeters, door openings), and counts (doors, windows, plumbing fixtures and other detected objects), each tied to the sheet it came from.
PDF sheet sets. Vector PDFs exported from CAD carry the original geometry and give the strongest results.
The sheet's scale is detected from the drawing and applied automatically, converting drawing-space geometry into real-world units. If a sheet needs manual scaling, it is flagged rather than silently guessed.
Export structured quantities into your estimating workflow. Kamai produces the quantities; pricing, production rates, and bid strategy stay in your estimating tool.

See for yourself

Bring a sheet. See what Kamai sees.