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Cadpilot

Cadpilot - image-driven CAD replication. Upload 2D engineering drawings, get back an editable parametric 3D model with STEP AP242 output, build123d source, and a written assumptions list. It stops and asks when unsure — and runs privately so drawings never leave your intranet.

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Cadpilot turns 2D engineering drawings into 3D models you can actually edit. Upload your drawings, and it rebuilds the part as a parametric CAD model — then hands over STEP AP242, build123d source code, and a written list of every assumption it made. When it's unsure about something, it stops and asks.

Replicate engineering drawings into 3D models that can be edited.

A scanned 2D drawing of a bracket — the input to Cadpilot

What is Cadpilot

Feed it 2–6 complete drawings of a part. Cadpilot reads the views and dimensions, rebuilds the geometry as a parametric model on the OCCT kernel, checks its own work against the original views, and delivers:

  • STEP AP242 and STL for downstream tools
  • build123d parametric source — dimensions are live parameters, not baked numbers
  • A dimensions & assumptions document — every default value it filled in, stated openly
  • A local interactive preview in the browser, nothing to install

Three kinds of "image-to-3D" — only one belongs in the shop

Most AI image-to-3D output is for eyes, not machines:

  • Mesh / STL — looks photo-realistic, but hole spacing is never guaranteed. Good for renders, useless for machining.
  • STEP without a feature tree — mathematically correct, but with no modeling history. Any change means starting over.
  • Cadpilot's delivery layer — a build123d parametric feature tree. Change a dimension and the model regenerates, like editing a cell in Excel and watching the formulas recompute.

The test it holds itself to: is the output for people to look at, or for machines to eat?

How it works

1. Drawing understanding — views are segmented automatically, dimensions read, sections and detail views handled, title blocks stripped out.

2. Parametric modeling — geometry is built in order (base body → subtractive features → patterns → fillets) as build123d code, executed on the OCCT kernel.

3. Compare & converge — the model is re-rendered from the original drawing's viewpoints and overlaid for comparison, with hard checks on dimensions. Deviations are corrected automatically.

4. Delivery — STEP AP242, STL, parametric source, the assumptions list, and an in-browser preview that runs locally.

Why multiple drawings? A single view is mathematically underdetermined — the same circle could be a through-hole, a boss, or a sphere. Multiple views cross-confirm until the model converges.

It stops and asks when unsure

This is the part most AI tools skip.

  • Interactive confirmation — when a judgment scores below a confidence threshold (say, a section view at 0.55 against a 0.60 threshold), Cadpilot pauses and waits for you to click, instead of guessing.
  • An assumptions list — undimensioned sizes get engineering-convention defaults, stated explicitly: 6061-T6 material, rib thickness, R6 base fillets. Nothing silent.
  • A dual-loop self-check — bad generated code is repaired automatically, then verified by render-and-compare. Anything that can't be fixed escalates to a human.
  • An honest metric — Cadpilot tracks its "one-shot usable rate": the share of parts usable for quoting and reference without modification. The north-star target is ≥40%, and it's reported as-is.

Cadpilot rebuilding a part as parametric build123d code

Render-vs-drawing overlay comparison

A worked example

The site ships with a built-in demo: two scanned blueprints of a retired equipment bracket — three views, a section, a detail view, and four undimensioned sizes.

  • Cadpilot paused on a projection judgment it wasn't confident about; the human confirmation avoided a mirrored part.
  • Delivered with a hole spacing corrected from 88.0 to 90.0 against the drawing, and a final profile deviation of 0.4%.
  • After review, changing one parameter in the source (BOLT_X, BOSS_Z, RIB_T) and re-running regenerates the part.

Best suited to medium-complexity 3-axis CNC machined parts. The demo data is built-in sample material, not customer work.

Your drawings never leave the intranet

  • Private deployment — a single machine via docker compose; drawings don't touch any cloud.
  • No training on your drawings — customer data is never used for training.
  • Open standards, no lock-in — STEP AP242 in and out, open-source kernel, and the generated source is plain build123d Python.
  • Escalation by default — repeated failures route to human review automatically.

Safety-critical parts still require review by a licensed engineer before manufacturing — Cadpilot says so itself.

Cadpilot delivery view — files, parameters and assumptions

Try Cadpilot


Built for real needs, because real needs are always valuable.