Research & Reference

Follow one order through an 18-machine shop, from RFQ to shipment. What the business looks like, where the bottleneck lives, and how CloudNC fits.

$61B in cognitive labour across US factories. $24B machinist wedge alone. Every role, wage, and assumption tagged to BLS source.

Global factory cognitive labour is ~5× the US market, wage-adjusted. Derived from CIMdata machine tool consumption and OECD wage data.

10% of US machinists retiring annually. No replacement pipeline. BLS occupation data modelled through 2035.

Bottom-up count of CNC facilities across the US and global market. Machine count and shop-count TAM derivation.

The arithmetic of reshoring manufacturing to the US. Defence industrial base demand and the role of AI automation.

Four converging forces: machinist retirement cliff, agentic AI inflection, reshoring boom, and defence industrial urgency.

Why CNC toolpath generation is a hard combinatorial problem. The search space, the constraints, and why it resisted automation for 40 years.

AI that generates CNC machining programmes from a 3D model. Gets 80% of the way there in minutes. The machinist does the last 20%.

30+ CAM packages exist. 2 integrations live, 11 by end of 2026. Each integration unlocks a new market segment without new R&D.

Real usage data from real machine shops. Adoption patterns, time savings, and customer testimonials.

Structural disincentives at every layer of the CAM value chain. Revenue fragmentation, rented intelligence, and failed attempts.

Detailed profiles of every AI CAM entrant. Technical approach comparison. Honest assessment of CloudNC's gaps.

$108.5M invested across three phases. Post-launch: 91% gross margin, 5.5× growth, 12.9-month CAC payback.

ICP GRR 93%, churn decomposition, CAC payback, LTV:CAC analysis, and the expansion flywheel model.

5-channel land model with observed conversion rates. $327K/month today to $6.8M/month by Dec 2028. Expansion is 71% of closing ARR.

Quantified CO₂ reduction from reduced machining waste and scrap. Bottom-up model with sourced emissions factors.

Full engineering roster, domain expertise breakdown, go-to-market org, and board composition. 62 people across 9 sections.

Full cap table, Top 10 shareholders, governance mechanisms, board composition, and 35-item diligence checklist.