https://adam.new/). We're building AI agents for mechanical CAD software. We’ve built the company on two fundamental beliefs:
- AI will be the primary medium for creating mechanical designs just like it is in software today.
- The best paradigm for CAD generation is to generate CAD as code (text -> code -> CAD).
We’re building CADAM, an open source Text to CAD platform. It's a React app (TanStack Start) with a Supabase backend for auth, database, and file storage. Think of it like AI TinkerCAD.
Demo: https://www.youtube.com/watch?v=iESOr7EGWqk Try it: https://adam.new/cadam/
What it does:
- Generates parametric 3D models from natural language, with support for both text prompts and image references.
- Outputs OpenSCAD code with automatically extracted parameters that surface as interactive sliders for instant dimension tweaking
- Exports as .STL or .SCAD (plus OBJ, GLB/GLTF, FBX, and DXF)
Under the hood:
- One agentic endpoint with two modes that swap system prompts and tools: a parametric mode that writes/edits OpenSCAD via a build_parametric_model tool, and a mesh mode that generates 3D textured meshes.
- Simple parameter tweaks bypass the model entirely; adjusting a slider does a deterministic regex update on the SCAD source, requiring no LLM call.
- Model-agnostic via the Vercel AI SDK: Anthropic (Claude), Google (Gemini), and OpenAI/others through OpenRouter, with adaptive thinking auto-enabled on newer models. Surprisingly, in our evals Gemini 3.1 Pro is the top model.
- Runs fully in-browser by compiling OpenSCAD to WebAssembly (in a Web Worker, so the UI never blocks) and rendering with Three.js via React Three Fiber
- Supports BOSL, BOSL2, and MCAD libraries, plus custom font support (Geist) for text in models
Future improvements:
- Support both build123d and CadQuery. This will allow us to move beyond CSG primitives to constraint-driven modeling and provide direct comparisons to other code-as-CAD primitives.
- Better spatial context: UI for face/edge selection and viewport image integration to give LLMs spatial understanding
You can clone the repo and run it locally! Contributions are very welcome.