Manufacturing has spent decades automating the physical work of making parts. Machines can cut metal with extraordinary precision, production lines can operate around the clock, and increasingly sophisticated software can control almost every stage of the process.
But some of the most important decisions still depend heavily on skilled people. Before a CNC machine starts cutting, someone has to determine how a part should be made, which tools to use, how it should be held and what machining strategy will produce the right result. That programming work can become a bottleneck, particularly as manufacturers face pressure to increase output without a corresponding increase in skilled labor.
UK-based CloudNC has spent years trying to automate more of that decision-making. The company has now raised $20 million in a Series B extension led by Nimble Ventures, bringing its total funding to $128 million as it moves its AI-powered manufacturing software into a broader commercial phase.
Taking AI Into CNC Programming
Founded in 2015 by Theo Saville and Chris Emery, CloudNC has focused on one of the more complex parts of precision manufacturing: translating the design of a component into instructions that a CNC machine can actually execute.
Its flagship product, CAM Assist, works alongside established computer-aided manufacturing software rather than asking manufacturers to replace the systems they already use. It can analyze a part and generate machining strategies and toolpaths, including decisions around tools, cutting directions, feeds and speeds. The programmer remains responsible for reviewing and approving the proposed approach before it reaches the machine.
That human role is important. CloudNC is not positioning CAM Assist as a replacement for experienced machinists and CAM programmers, whose knowledge can take years to develop. Instead, it is automating repetitive first-pass work so those people can spend more time on difficult parts, production problems and decisions where experience matters most.
The approach is beginning to move beyond early adoption. CAM Assist is now used by more than 1,000 machine shops globally, and CloudNC says the software can integrate with widely used platforms including Autodesk Fusion, Mastercam, Siemens NX, GibbsCAM and SolidCAM. The company has also expanded the product with CAM Assist 2.0, giving programmers greater oversight of AI-generated strategies before sending approved toolpaths back into their existing CAM environment.
Manufacturing Has a Productivity Problem
CloudNC’s opportunity is being shaped by pressures much larger than CNC programming alone.
Manufacturers are being asked to produce more while dealing with skilled-worker shortages, supply-chain uncertainty and growing pressure to bring strategically important production closer to domestic markets. Those challenges are particularly visible in industries such as aerospace, defence, automotive and energy, where precision components can be difficult to produce and experienced machining talent is valuable.
For a machine shop, that creates pressure at several points in the workflow. Winning a job requires understanding whether a component can be manufactured profitably, producing an accurate quote and then programming the machines required to make it. Delays at any of those stages can reduce throughput even when expensive CNC equipment itself is available.
CloudNC is effectively trying to increase the productivity of the people around those machines.
That also makes its use of AI different from the wave of enterprise copilots designed primarily around text and office work. CAM Assist operates inside a physical production process where an incorrect decision can waste material, damage tooling or create a component that fails to meet specification. The value of the software therefore depends not only on generating an answer quickly, but on producing machining strategies that skilled users are willing to trust and approve.
Expanding Beyond Programming
The new funding will allow CloudNC to push further into that workflow.
Alongside wider adoption of CAM Assist, the company is preparing to launch Quote Agent, an AI product aimed at another labor-intensive part of running a machine shop: deciding how much a new job should cost and whether it is worth taking.
Quoting can require manufacturers to review drawings, assess manufacturability, estimate machining time and understand the risks associated with producing a component before a contract has even been won. Moving too slowly can mean losing the work, while getting the estimate wrong can erode the margin once production begins.
Quote Agent is designed to help manufacturers assess those jobs faster and more consistently while keeping the final commercial decision with the user. CloudNC says the product will be available later in 2026, extending its automation strategy from programming the work to helping manufacturers decide which work to take in the first place.
The company will also use the $20 million investment to strengthen its go-to-market operations and expand in existing and new markets. Nimble Ventures led the round, with participation from Calculus Venture Capital, Entrepreneur First and LM Ventures, Lockheed Martin’s venture capital arm.
From AI Assistant to Manufacturing Infrastructure
CloudNC’s next challenge is less about proving that AI can help generate machining strategies and more about making that technology part of everyday manufacturing.
More than 1,000 shops already using CAM Assist gives the company a base to build from, but precision manufacturing is a fragmented market with different machines, software environments, materials and production requirements. Scaling across that landscape requires software that can fit into existing workflows without forcing manufacturers to rebuild the systems and expertise they already rely on.
CloudNC appears to understand that constraint. Its strategy has been to integrate with established CAM platforms and keep experienced programmers involved in the process rather than trying to automate the factory in one step.
There is also a larger industrial story developing around the company. As governments and businesses put more attention on reshoring, defence capacity and resilient supply chains, increasing manufacturing output cannot depend entirely on adding more machines or finding more skilled workers. Existing factories will also have to become more productive with the resources they already have.
That is where CloudNC’s technology could become more consequential.
The company’s $20 million round is not particularly large by current AI funding standards, but the market it is addressing is enormous and deeply embedded in the physical economy. Every aircraft, vehicle, industrial system or piece of defence equipment ultimately depends on manufacturers being able to turn designs into real components efficiently.
CloudNC is betting that AI can compress the expertise and repetitive work surrounding that process without removing the people who understand it best.
If it can scale that model, AI’s impact on manufacturing may be measured less by fully autonomous factories and more by something immediately practical: helping existing factories quote faster, program faster and produce more with the people and machines they already have.