CloudNC has secured $20 million in new capital to scale its AI precision machining technology across global supply chain networks.

The investment round was led by US venture investor Nimble Ventures, with participation from Calculus Venture Capital, Entrepreneur First, and LM Ventures, the venture capital fund of Lockheed Martin.

Founded in 2015, CloudNC operates from headquarters in London and an active production facility in Chelmsford. The company previously drew backing from Atomico and Episode 1 Ventures, alongside strategic partnerships with Autodesk and Lockheed Martin.

Precision component suppliers face pressures to balance tight engineering tolerances with compressed delivery schedules. CloudNC designs its lead software product, CAM Assist, to automate computer numerical control (CNC) programming—generating machining strategies and toolpaths from computer-aided manufacturing models to accelerate production runs.

Automating CNC programming for supplier networks

The software shortens the transition phase between technical part design and factory production, allowing machinists to increase physical component output.

CloudNC reports that CAM Assist is now active across more than 1,000 machine shops globally, including several hundred facilities in the US. Confirmed commercial users include Lockheed Martin and Major Tool and Machine.

Theo Saville, CEO and co-founder of CloudNC, said: “Machine shops everywhere are under pressure to quote and program faster, and deliver more with the people and machines they already have.

John Burbank, founder of Nimble Ventures, added that automated CNC workflows will support “massive increases in onshoring of manufacturing and global production” for precision industrial supply bases.

CloudNC says it will direct the capital injection into go-to-market operations, technical support infrastructure, and partner activity across international regions.

AI quoting targets procurement turnaround times

CloudNC is expanding its software line with Quote Agent, an AI-assisted estimating tool scheduled for release later in 2026.

Preparing job estimates represents a major operational drag for manufacturing suppliers. Evaluating incoming technical drawings, calculating cycle times, and establishing part pricing remains heavily manual, exposing supply shops to administrative delays or miscalculated margins once components enter physical production.

Quote Agent applies AI to early-stage costing, enabling suppliers to return customer bids rapidly while standardising cost estimations.

“Quote Agent is a natural next step for CloudNC as we seek to accelerate global machining with AI,” says Saville. “CAM Assist already helps machinists get parts onto machines faster; Quote Agent will help shops assess new work, prepare quotes more efficiently and respond to customers with greater confidence.”

“We believe our AI can make quoting faster, more consistent and more scalable, helping manufacturers win more of the right work while keeping expert judgement firmly in control,” Saville added.

Knox Systems partnership advances FedRAMP authorisation

CloudNC is collaborating with Knox Systems to achieve FedRAMP certification for CAM Assist.

The compliance roadmap aims to clear CAM Assist for deployment by US government departments, defence contractors, and aerospace manufacturers operating under federal data governance rules. 

Authorisation, if granted, will permit public-sector and defence suppliers to deploy automated toolpath generation across regulated production workloads.

See also: Samsung taps Mistral AI models for semiconductor manufacturing

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Samsung has partnered with Mistral AI to deploy on-premises models across its semiconductor manufacturing and engineering operations.

The agreement was announced during the bilateral state summit held in Paris between South Korea and France. Samsung will integrate Mistral’s software suite – including its flagship Mistral Large model – into internal semiconductor facilities to build customised models for intelligence-driven factory infrastructure.

On-premises AI models for semiconductor fab infrastructure

The deployment relies on private enterprise installations to process sensitive engineering and operational records within Samsung’s computing perimeter. This architecture keeps proprietary technical data contained within company infrastructure, avoiding external cloud exposure while maintaining control over operational assets.

“Increasing complexities involved in AI chip design and manufacturing requires continuous innovation in semiconductor technologies,” says Young Hyun Jun, Vice Chairman and CEO of the Device Solutions (DS) Division at Samsung Electronics.

Mistral will provide Samsung with a specialised stack of software tools to assist in how processors are designed and produced.

“AI is reshaping how we build complex technologies, from silicon to software,” says Arthur Mensch, co-founder and CEO of Mistral.

“We are proud to support Samsung Electronics with our expertise in electronics and semiconductors, helping to improve how chips are designed and manufactured, and to accelerate technical progress across the global semiconductor and AI value chain.”

Defect detection and yield stabilisation

Samsung plans to deploy the targeted models directly to automated defect detection and fab machinery tuning. As semiconductor production processes advance, rapid data analysis inside the fab becomes necessary to maintain factory throughput.

The company expects targeted AI models to accelerate development cycles, improve manufacturing precision, and stabilise production yields across advanced memory and logic chips. The operational scope covers Samsung’s memory division, logic design units, and contract foundry business.

Samsung also led Mistral AI’s Series D funding round, securing a strategic equity stake to support long-term technical cooperation.

The lead investment expands cross-industry collaboration between silicon manufacturers and AI developers across advanced memory, logic, and foundry operations.

See also: Arm launches Total Design for Physical AI and robotics framework

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MG Ship has introduced an AI route optimisation and carrier selection module as logistics deployments demonstrate rapid cost and time returns.

The technical module targets global retailers and commercial shippers, pairing automated routing algorithms with carrier recommendation systems across international trade corridors. The deployment arrives as enterprise supply chain operators report measurable operational returns from machine learning tools, moving capital allocations away from speculative trials toward production deployments.

Measurable returns from deploying AI for logistics

Suki Cheung, CEO of MG Ship, will present deployment metrics during a panel discussion at the upcoming WMX Asia conference. Cheung will join executives from Pos Malaysia, Omniva, and OnyX Space for the session, titled AI Beyond the Hype: Measurable Results in Logistics Today.

“Too many AI conversations in logistics remain focused on future possibilities,” said Cheung. “The reality is that AI is already delivering measurable business outcomes today. Leading organisations are reducing transportation costs, improving forecast accuracy, increasing warehouse productivity, and achieving payback within months rather than years.”

Industry operational data indicates that initial investment returns are concentrating across three primary workflows:

• Dynamic route planning has reduced enterprise fuel consumption by 15–20 percent, improved transit speeds by 15–25 percent, and lowered overall transportation costs by 12–22 percent, with capital payback reached within three to six months.
• Predictive demand forecasting has reduced projection errors by 20–40 percent, improved planning accuracy by up to 35 percent, and decreased excess inventory by 20–30 percent within six to 12 months.
• Automated freight documentation processing has cut manual task duration by up to 85 percent, recovering initial expenditure inside three to six months.

Over five-year deployment cycles, enterprise adopters have recorded average operational expense reductions between 10–25 percent, accompanied by warehouse productivity gains of 25–35 percent.

Routing algorithms and carrier scoring

MG Ship built the new routing capability directly into its visibility and supply chain intelligence platform, which serves retailers, manufacturers, and freight operators across multiple international markets. The base system synthesises live cargo telemetry with trade intelligence, risk monitoring, and predictive analytics to support operational planning and trade financing.

The route optimisation engine processes live and historical lane transit logs, weather patterns, air and ocean port congestion indicators, customs risk alerts, and transit reliability data. Shippers receive automated recommendations identifying low-cost, low-risk transit paths.

Carrier evaluation features rank transport providers per lane and service tier. Rather than selecting capacity purely on spot freight pricing, the system scores carriers against historical on-time metrics, transit consistency, exception occurrences, claims rates, available volume, and total cost-to-serve.

Logistics teams can also execute scenario simulations prior to peak shipping quarters. The software models lead times, service levels, freight spend, and risk exposures under alternative carrier allocation rules.

Early enterprise implementations demonstrate lower lead-time variance, reduced expedited freight expenditure, and improved on-time-in-full delivery rates.

Cheung stated that the platform “does not simply tell businesses where their cargo is”, adding that “it recommends the best route, the right carrier, and the lowest-risk option based on real-time conditions, helping organisations make faster and more profitable decisions.”

See also: OneRail uses Nvidia AI for real-time last-mile delivery optimisation

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and is co-located with other leading technology events including the Cyber Security & Cloud Expo. Click here for more information.

AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.

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