Miju LabsThe interesting fact about mechanical CAD is not that the vertical is empty — seven of these eight verticals are empty. It is that the tool vendor who could close it has publicly declined to.
Autodesk's Project Bernini was trained on ten million 3D shapes described as "publicly available data, CAD objects, and organic shapes" (Autodesk Research). Autodesk sits on more customer geometry than any organisation on earth and has made no claim that it trained on any of it — almost certainly because its enterprise contracts forbid it. Then in February 2026 it put $200M into World Labs (TechCrunch, Autodesk). That is a company buying capability, not one sitting on a moat.
Compare Chip design and EDA, where Cadence's JedAI platform openly "aggregates waveforms, coverage reports, timing analyses, and physical layouts into a unified training data repository, creating a compounding data moat" (SemiAnalysis). Same structural position, opposite behaviour. In EDA the tool vendor has won the data layer; in CAD the door is open — and AEC Magazine names why it matters: "there is a limited amount of data available to train foundational 3D models", because unlike text and images, 3D needs "professional-grade CAD objects" (AEC Magazine).
What the data actually is
Not geometry. Geometry is what the academics already collected. The product is manufacturing judgement about geometry, which nobody has collected at all.
The gap is visible in the benchmarks themselves. BenchCAD (University of Virginia and others, 2026) is 17,900 execution-verified CadQuery programs across 106 industrial part families, 49% anchored to ISO/DIN/EN/ASME/IEC standards. GPT-5.3 thinking reaches 0.865 on Code Edit, but Gemini 3.1 Pro manages only 0.587 on Vision QA, and the paper concludes that frontier models "often recover coarse outer geometry but fail to produce faithful parametric CAD programs" (arXiv 2605.10865).
MechVQA (BAAI and CAS) is 3,281 mechanical drawings and 20,778 QA pairs, generated by an MLLM pipeline with "mechanically trained graduate students" doing secondary verification — explicitly not paid professional annotation. Best model 84.85% overall, 75% on hard items (arXiv 2605.30794).
Read those two methodology sections together and the wedge names itself. Both are academic, both used cheap annotation, and neither asks the question a manufacturing engineer is paid for:
| Line | What it asks | Why no one has it |
|---|---|---|
| DFM verdicts | Can this part be made, by what process, at what cost | Requires someone who has quoted parts for a living |
| Tolerance stack-ups | Where the assembly binds, and which dimension to loosen | Judgement, not computation; the answer depends on the process |
| Process selection | Cast, machine, print, or fabricate — and why | Sits in the heads of shop estimators, not in any corpus |
| Failure narration | This design failed; here is the sequence of reasoning that predicted it | Needs a physical outcome to anchor against |
Proof scores 4: two unsaturated public numbers to beat and no competitor to displace, one notch below Video, motion and VFX only because BenchCAD's authors are iterating and 84.85% on MechVQA is closer to done than 34.65% on VEBench.
Is anyone buying
Yes, and cheaply, which is the whole problem and the whole opportunity. Budget scores 4.
- GDPval includes mechanical and industrial engineers among its 44 occupations (OpenAI).
- Mercor lists Mechanical Engineer at $65–$80/hr, 20 hrs/week, to "create and assess complex problems in mechanical engineering" and "evaluate AI-generated responses for conceptual accuracy, technical rigor, and domain relevance" (Mercor).
- Its PhD tier — Engineering Research Experts, mechanical/electrical/civil — pays $50–$70/hr for "structural analysis, electromechanical systems, simulations (FEA/CFD), or CAD/PCB design" (Mercor).
- xAI's Mechanical Engineering Tutor required a Master's or PhD and paid $45–$75/hr, median $60 (Glassdoor listing).
Now the uncomfortable comparison. A PhD mechanical engineer is worth less per hour to a lab than a four-year civil engineer ($95–170/hr, see Architecture, engineering and construction) or a two-year investment banker (Investment banking and financial modelling). That says CAD and manufacturing are being purchased as generic STEM reasoning — interchangeable with physics tutoring — rather than as a vertical with its own artefacts.
Repricing that is the business. A generic STEM tutor cannot tell you whether a boss feature will short-shot in injection moulding. A manufacturing engineer can, and nobody is paying them to.
No system card, model release or disclosed contract cites purchased CAD or manufacturing expert data. The demand case here rests entirely on job postings with pay bands and one occupation list. That is true of every niche in this set except the rate-card strength of Video, motion and VFX — treat "the lab is buying" as an inference from what labs advertise, not from what they have signed.
Getting the experts
Reach scores 5, on the strength of one number nobody else in this atlas can match at this size. GrabCAD has 16 million community members and 6 million shared CAD files — a working population, publicly indexed, already in the habit of publishing their own parts under their own names. It functions the way GitHub review history functions for Senior code review: a free, verifiable demonstration of the exact skill being bought.
Around it: Practical Machinist, where estimators and shop owners argue about processes; r/cad, r/MechanicalEngineering and r/SolidWorks; 3DEXPERIENCE World; and NTMA and PMA for job shops, which is the channel to DFM knowledge that lives in shops rather than OEMs.
BLS counts 298,500 US mechanical engineers at a median $104,110/yr, growing 11% (BLS Occupational Outlook Handbook; no URL was captured in the research, so treat the citation as second-hand) — roughly $50/hr on a 2,080-hour year against an observed $65–80/hr AI-data rate. A 1.3–1.6x arbitrage: thinner than Architecture, engineering and construction's, thick enough to recruit on, better than Senior code review's.
What it costs to run
Cost scores 4, and this is the page where the capital question has a real answer rather than a rhetorical one.
The base business needs no rig. SolidWorks and Fusion seats sit in the low thousands per seat per year at reseller list (reseller price list) [WEAK — reseller pricing]. Standards are a licensed cost — BenchCAD's 49% anchoring to ISO/DIN/ASME shows the standards layer is a legitimate substrate, and one you pay for. Call it a five-figure annual software and standards line against a $50/hr labour floor. That is a labour business.
The differentiated business needs a mill, and that is a choice. Closing the physical loop — the model said this part was manufacturable, here is the part, here is why it failed — requires a CNC mill or a good FDM/SLA setup. Nobody in either directory is doing it. That is capital, and the honest framing is five figures, not seven: one machine, one operator, one small space. Compare Life-science wet lab, where the equivalent move costs a building and each experiment runs into the thousands, or Skilled trades and field service, where a representative rig means panels, condensing units, PLCs, a shop and insurance before the first data point.
That distinction is why cost is 4 here and 1 there. A five-figure capital line that upgrades an already-viable labour business is a strategy. A capital line you must clear before you can sell anything is a different company.
Who is already there
Room scores 5. Neither the 37-vendor RL directory nor the top-50 human-data listing contains a CAD or mechanical specialist (rl-list, alignlist). The adjacent companies — Leo AI, Neural Concept and the broader AI-for-mechanical-engineers stack [WEAK — vendor blogs] (Leo AI) — are data-starved applications, and are customers rather than competitors.
Defense scores 4. Manufacturing knowledge is tacit, held by people who have quoted and cut parts; standards revise on published cycles, so the dataset decays on a schedule; and the physical-verification loop cannot be replicated by a horizontal without buying the same machine.
What would kill it
Autodesk changes its mind. The entire favourable read here rests on a tool vendor declining to mine its own corpus. One contract amendment and a company with every customer's geometry is in your market.
The labs keep buying it as generic STEM. If mechanical engineering stays a $60/hr tutoring line item, there is no vertical to sell — only a supply position inside Mercor's. The repricing is a bet, not an observation.
The academics get there first. BenchCAD and MechVQA are cheap to extend. A second round of graduate-student annotation covering DFM takes your headline before you publish it — and employer NDAs mean you must reconstruct parts rather than scrape them, which costs engineer hours the academics do not spend.
The first ninety days here
Recruit 50–80 people, weighted toward job-shop estimators and manufacturing engineers rather than design engineers — the judgement you sell lives closer to the machine than to the model tree. GrabCAD contributor histories and Practical Machinist are the two lists; pay $85–100/hr against a $50/hr floor.
Build the benchmark neither academic group built: a DFM and tolerance benchmark with a physical ground truth. Two hundred parts, three engineers each predicting manufacturability, process and cost — then cut a subset and publish where the predictions and the parts disagreed. That artefact cannot be synthesised and cannot be made without the machine, which is exactly the property The specialist wedge wants in a first release. See The first ninety days.
Where the record is thin
The Mercor and xAI bands are recruiting pages, not invoices, and nobody has published what a CAD evaluation set sells for at any buyer.
SolidWorks seat pricing comes from a reseller list rather than Dassault, and the BLS figures reach this page without a captured URL. The claim that Autodesk does not train on customer geometry is an inference from an absence in Bernini's announcement, not a disclosure — it is the load-bearing assumption here and deserves a direct question before anyone commits capital. The [NOTHING FOUND] on competitors comes from directories that are SEO properties rather than registries.