CloudNC has raised $20 million as manufacturers search for ways to produce more without finding thousands of additional specialists. The British startup believes artificial intelligence can remove repetitive planning work while keeping experienced machinists responsible for final decisions.
The Series B extension was led by Nimble Ventures, with Calculus Venture Capital and Entrepreneur First also participating. LM Ventures, Lockheed Martin’s venture arm, joined the round as CloudNC pushes deeper into advanced manufacturing markets.
CloudNC will use the funding to expand CAM Assist, strengthen sales operations, and enter additional manufacturing markets worldwide. The company is also developing Quote Agent, which targets another slow process occurring before machining even begins.
That broader strategy makes the funding more interesting than another investment round for an artificial intelligence software company. CloudNC wants to automate several decisions that still depend heavily on scarce manufacturing knowledge and experienced human workers.
CNC machining uses computer-controlled equipment to cut materials into precise components for industries including aerospace, energy, and defense. However, these advanced machines still require people to make many complicated decisions before cutting actually starts.
A programmer must decide how to hold each component, which tools should approach it, and which speeds work safely. Traditional computer-aided manufacturing software helps manage that process, but skilled workers still perform much of the planning manually.
CloudNC built CAM Assist to handle more of that first-stage thinking before the programmer approves the final strategy. The software analyzes a component and generates machining approaches and toolpaths inside existing computer-aided manufacturing environments.
It can suggest tools, cutting directions, feeds, speeds, and other decisions normally requiring careful manual work from programmers. Users can then inspect the proposed strategy, make adjustments, and approve everything before sending instructions toward production machines.
That human review remains important because CloudNC is selling increased productivity rather than completely autonomous manufacturing without experts. Experienced machinists still understand unusual materials, customer requirements, machine behavior, and production problems better than general software.
CloudNC instead wants its technology handling repetitive setup work that consumes valuable time inside busy manufacturing facilities. The company says CAM Assist can complete much of a machining program before an experienced worker finishes reviewing it.
More than 1,000 machine shops worldwide already use CAM Assist after the product began expanding commercially. CloudNC says those customers use the technology to reduce programming time while keeping people involved throughout important decisions.
That adoption arrives when manufacturers face growing pressure to produce more complicated products with limited skilled labor available. Finding experienced CNC programmers can become particularly difficult because developing their knowledge often requires years of practical training.
The United States provides an important example because manufacturing employers continue struggling with large numbers of unfilled positions. Deloitte reported roughly 409,000 manufacturing vacancies during August 2025, highlighting the size of the workforce challenge.
The industry could need millions of additional workers through 2033 if domestic manufacturing investment continues expanding significantly. Deloitte estimates nearly 1.9 million positions could remain unfilled unless longstanding workforce challenges receive effective solutions.
That shortage makes tools like CloudNC more attractive because factories cannot simply hire experienced programmers whenever workloads increase. Automation can help existing teams process more work without asking manufacturers to replace every experienced employee with software.
This distinction matters because manufacturing knowledge remains difficult to capture inside a simple artificial intelligence prompt. Machinists must consider equipment limits, cutting tools, materials, tolerances, fixtures, costs, and customer expectations before approving production.
CloudNC has spent years developing technology around those specific problems instead of applying a general AI model afterward. The company operates its own manufacturing facility, giving engineers direct exposure to problems their software eventually needs to solve.
That experience also helps explain why CAM Assist integrates with software machinists already know instead of replacing everything. Current integrations include Mastercam, Autodesk Fusion, Siemens NX, GibbsCAM, and several other established manufacturing platforms.
The company is now extending the same automation idea into the commercial side of running machine shops. Quote Agent will help manufacturers evaluate incoming jobs before deciding whether they should accept or reject them.
Quoting can become another serious bottleneck because every potential job requires someone to estimate manufacturing difficulty and cost. Moving too slowly can lose customers, while poor estimates can leave shops accepting complicated work at unprofitable prices.
Quote Agent analyzes parts and drawings while helping manufacturers identify production risks and prepare customer-ready quotations more quickly. CloudNC says the browser-based service was designed specifically around the everyday requirements of CNC machine shops.
This expansion gives CloudNC a chance to automate more of the journey before a machine produces anything. It could eventually influence how shops evaluate work, prepare bids, program machines, and manage production efficiency.
That becomes particularly valuable as companies consider bringing more production closer to customers instead of depending heavily on imports. Greater domestic manufacturing requires machines, factories, suppliers, and enough skilled workers to make those investments genuinely productive.
McKinsey estimates the United States would require major manufacturing expansion to replace several strategically important imported product categories domestically. Some vulnerable categories would require domestic production to approximately double before fully matching current demand.
Yet adding physical manufacturing capacity without improving productivity could make existing worker shortages even harder to manage successfully. Manufacturers therefore need technology helping experienced employees accomplish more while training newer workers faster and reducing unnecessary manual steps.
CloudNC is positioning its software directly inside that challenge instead of promising factories an entirely automated future. Its products are designed to support people already operating complex machines rather than removing human judgment immediately.
That approach could prove easier for traditional manufacturers to adopt because it changes specific workflows without rebuilding entire factories. Companies can introduce AI alongside familiar machines and software while measuring whether actual productivity improves before expanding usage.
CloudNC has already expanded internationally, including opening a Shanghai office earlier this year for Chinese manufacturing customers. The company said one Chinese customer reduced programming time on representative parts by around 70 percent using CAM Assist.
Its next challenge will be turning early adoption into widespread use across thousands more manufacturers and machining environments. Every factory has different equipment and practices, making reliability more important than producing impressive results inside controlled demonstrations.
Competition will also grow because manufacturing software companies increasingly recognize artificial intelligence as an important productivity opportunity. Established platforms already have deep customer relationships and could add similar automation capabilities across their existing product portfolios.
CloudNC therefore needs to prove its specialized manufacturing knowledge creates an advantage that broader software companies cannot easily reproduce. Its own factory and years spent solving CNC problems provide a useful foundation, but commercial scale remains the larger test.
The $20 million investment gives CloudNC more resources to answer that question while manufacturing pressures continue building globally. If skilled labor remains limited, software that makes existing workers substantially more productive could become increasingly difficult for factories to ignore.
CloudNC is ultimately betting that manufacturing’s AI opportunity will look different from automation replacing entire groups of workers. The bigger near-term opportunity may involve giving scarce experts better tools and removing work that never required their expertise.
