PITCH.md

Chat CAD — Pitch Outline

"What if every mechanical engineer could describe a part in plain English, get a real B-rep model back in seconds, and have an AI critic check it for manufacturability before they ship it?"

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Slide 1 — The Problem

• Designing a mechanical part still takes 2–8 hours in SolidWorks for a trained engineer. Most of that time is the same patterns repeated: brackets, housings, mounting plates, fastener stacks.
• Junior engineers and product designers spend 40%+ of their week on these "boilerplate" parts that aren't the interesting work.
• AI CAD tools exist (KittyCAD, CadChat, Spline AI) but they generate mesh tris, not real B-rep models you can hand to a CAM package or machinist.

Slide 2 — The Insight

The bottleneck is not the kernel. OpenCascade has been open-source for 25 years and powers FreeCAD, Onshape, and IronCAD. The bottleneck is the interface between human intent and that kernel.

We bridge it with frontier LLMs treating CadQuery / OpenCascade operations as function-call tools, plus a multi-agent loop (planner → modeler → visual critic → DFM critic → standards critic) that catches mistakes before they leave the chat.

Slide 3 — What Chat CAD Does Today

One chat command produces real, exportable, machinable geometry:

• bolt_stack jt M6 12 50 → plate + 2 washers + threaded M6 bolt + hex nut, all real B-rep solids, ready for STEP export.
• turbojet jet 120 500 → 19 named sub-parts of a realistic axial-flow turbojet engine: spinner, nacelle, 8-stage compressor (rotor+stator), annular combustor, HP+LP turbine, afterburner, conv-div nozzle, shaft.
• naca wing 2412 80 30 → NACA 4-digit airfoil section, extruded.
• A natural-language brief in Design Agent mode → multi-step composition with on-the-fly visual checking via Claude vision.

Slide 4 — Technical Stack

Layer	Technology	Why
Kernel	CadQuery on OpenCascade (OCP)	Same B-rep family as Onshape & FreeCAD
Tool layer	140+ chat-callable operations	Primitives, booleans, sketches, assemblies, sheet metal, structural profiles, library parts, aerospace mockups
Multi-agent	5 agents on Claude/Gemini	Planner · Modeler · Visual Critic · DFM Critic · Standards Critic
Retrieval	TF-IDF knowledge layer	Org standards (M-spec rules, wall-thickness mins, etc.) auto-loaded into every prompt
Simulation	gmsh + scikit-fem	Real linear-elastic FEA + steady-state thermal in a subprocess
Viewport	Three.js + PBR + IBL	19 material presets, view cube, gizmos, section clip, exploded view
LLM	Anthropic / Google / Ollama / WebLLM	Cloud or fully local; no vendor lock-in
Deployment	Windows installer (.exe) or Docker	One-double-click install or one-line container

Slide 5 — What Differentiates Chat CAD

1. Real B-rep output, not mesh tris. STEP / STL / engineering-drawing PDF.
2. Multi-agent loop with a DFM critic — catches "wall too thin" and "sliver geometry" before the user ships.
3. Bring-your-own LLM — works with paid Claude/Gemini OR free Ollama (offline) OR free in-browser WebLLM. Customer never has to send their IP through a vendor they don't trust.
4. Domain-specific recipes — turbojet, gear_train, bolt_stack, piston_engine produce ready-to-export assemblies in one command. Generic AI CAD can't do this.
5. Real FEA on real geometry — most AI CAD tools stop at "looks like a part." Chat CAD will run a linear-elastic solve on it.

Slide 6 — Use Cases

Customer	Workflow	Value
Junior mech engineer	Boilerplate brackets, mounts, plates	4 hr → 15 min
3D-print hobbyist	"Make me a wall-mount for X"	No CAD class needed
Aerospace concept designer	Turbojet / propeller / NACA mockups for proposals	1 day → 1 hour
Educator	Live-build during a lecture from a chat	Single tool replaces 4

Slide 7 — Why Now

• LLM tool use crossed the reliability threshold in mid-2024 (Claude 3.5 Sonnet was the inflection point). Before then, a chat-driven CAD was a research demo. Today it can be a product.
• WebGPU shipped in browsers in 2023, making real-time PBR + IBL in the browser viable.
• OpenCascade's Python bindings stabilised. CadQuery 2.4 + cqkit are production-ready.
• 200K+ engineers laid off in the last 18 months. The market for "AI copilots that 10x mid-level engineering work" is wide open.

Slide 8 — Where We Are vs Competitors

	Chat CAD	KittyCAD	CadChat	SolidWorks
Real B-rep output	✓	✓	partial	✓
Chat / NL interface	✓	✓	✓	—
Multi-agent + DFM critic	✓	—	—	—
Real FEA on the same geometry	✓	—	—	$20k/seat add-on
Bring-your-own LLM (local Llama)	✓	—	—	—
Windows installer / offline mode	✓	—	—	✓
Aerospace recipes (turbojet etc.)	✓	—	—	—
Enterprise drawing standards	—	—	—	✓
30 years of customer test data	—	—	—	✓

Slide 9 — Defensibility / Moat

Honest answer: we don't have a deep moat yet. We have a head start. What we'd build into a moat over the first 12 months:

1. Fine-tuned modeler agent on a captured dataset of "brief → CadQuery ops" pairs. Right now we leverage frontier LLMs; over time we own the model.
2. Vertical-specific recipe library — partner with one industry (aerospace concept design, custom fixturing, or 3D-print on-demand) and own the recipe catalogue for that vertical.
3. Customer-generated knowledge corpus — the RAG layer is already built. Every customer's standards file becomes a personal moat that discourages switching.

Slide 10 — Ask

• Seed: $500k–$1.5M
• Use of funds: 1 founding engineer hire (kernel) + 1 ML engineer (fine-tune the modeler) + 12 months runway + cloud + 3 pilot customers
• Outcome by month 12: 10 paying customers at $200–$500/mo, $20–60k ARR, validated wedge, ready for Seed-extension or Series A on real growth data
• Outcome by year 3: $1–3M ARR, $10–30M valuation. Acquired by an enterprise CAD vendor OR continues independently.

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Honest Caveats (Don't Hide These In Diligence)

1. Open-source kernel = no IP moat on the geometry layer. Anyone could build on the same foundation. Our moat is the agents, RAG, recipe library, and brand.
2. Frontier-LLM dependency for the best results = compute cost per user is non-trivial. The Ollama/WebLLM fallback mitigates but doesn't eliminate this.
3. Not aerospace-certified. Will not be hospital/aerospace/automotive for safety-critical parts until 5+ years of test data and a real QA process.
4. Single-developer codebase = bus factor of 1 until the first hire.

These caveats belong in the deck. They build trust with sophisticated buyers and stop dumb objections during diligence.

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Demo Script (3-minute)

1.  Launch the .exe → browser opens to a clean white viewport
2.  Type: bolt_stack demo M8 15 60
       → 5 parts appear: plate + 2 washers + threaded M8 bolt + nut
3.  Right-click the bolt → "Mirror about XY" → second bolt
4.  Switch to RENDER ribbon → "Polished steel" → Apply to all
5.  Click Drawing PDF → 4-view engineering drawing downloads
6.  Switch to SIMULATE ribbon → Click the plate → Run FEA
       → real stress numbers in 8 seconds
7.  Type in chat: "turbojet engine, 200 mm fan, 600 mm length"
       (in Design Agent mode with Claude)
       → 19 sub-parts appear, agent picks tools, visual critic checks
8.  Switch to Materials ribbon → Apply "Brushed aluminum" + "Sky" env
       → engine catalog shot
9.  Show: this entire flow took 90 seconds. SolidWorks equivalent: 4–8 hours.

This is the demo that closes the meeting. It is already possible in the software you have right now. Practice it, record it, send it.