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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NVIDIA has agreed to acquire Hugging Face for $12.93 billion to scale the open-source model repository’s platform and infrastructure.

The transaction targets platform growth and infrastructure investment, aiming to expand AI access for enterprise developers, software engineers, and research institutions globally.

Built over the past decade by Clem Delangue, Julien Chaumond, Thomas Wolf, and their engineering team, Hugging Face serves as the primary home for the open model developer community.

Platform metrics show more than 18 million developers, researchers, and creators share more than three million models, 500,000 datasets, and one million applications. Commercial adoption includes more than 200,000 companies using the environment to discover, evaluate, customise, and deploy AI models.

Hardware neutrality and multi-cloud commitments

NVIDIA stated that Hugging Face will remain an open platform for the entire AI sector. Developers will retain full control over their selection of models, software frameworks, cloud providers, inference services, and computing hardware.

NVIDIA hardware will not be mandatory to build on or deploy software through the platform. The service will maintain operational support for alternative accelerators, multi-cloud architectures, and open-weight models from all third-party builders.

Jensen Huang, Founder and CEO of NVIDIA, said: “Hugging Face will remain an open platform for the entire AI ecosystem. Developers will choose the models they want, the frameworks they want, the clouds and inference service providers they want, and the computing platforms they want.

“NVIDIA compute will not be required to build on or deploy through Hugging Face.”

Open-weight models and distributed development

Huang noted a recent open letter he co-authored regarding the role of open weights in the AI economy. The position argued that open weights broaden AI access and ensure technical leadership remains distributed across companies, academic institutions, and developer communities.

Under this operational model, commercial businesses, startups, universities, and public bodies can build on advanced capabilities without the expense of training baseline models from scratch.

The approach allows organisations to match specific models to operational tasks across factories, hospitals, farms, classrooms, and commercial businesses, while addressing cybersecurity and data sovereignty requirements.

Julien Chaumond, Co-Founder and CEO of Hugging Face, commented: “AI is at an inflection point. Open-source AI can become less relevant in the coming years if the big closed labs run away with it, or it can become the foundational fabric of the next phase of human civilisation.

“Those are vastly different outcomes, and we need the critical mass to ensure we give our collective best shot to the second outcome. Given Jensen Huang’s stance on open source AI and how he stepped up to defend it when it was under threat earlier in the summer, NVIDIA was the only partner we truly considered.”

Infrastructure expansion and brand preservation

NVIDIA stands as the largest contributor of open models and data to Hugging Face, with a portfolio of more than 500 open models and more than 250 open datasets. The company builds its libraries, tools, and models openly to allow external engineers to inspect, modify, and build atop the software.

Technical integration will focus on applying NVIDIA infrastructure and engineering resources to improve repository reliability, safety controls, model evaluation tooling, inference execution, and deployment pipelines.

“I am honored that Clem came to me as he considered the next chapter of Hugging Face and believed NVIDIA would be a great home for the company, its community and the future of open models,” Huang stated.

Hugging Face will retain its independent brand identity following the completion of the transaction, with the existing team continuing operations across multi-cloud and multi-accelerator environments.

“This gives fuel to our long-term vision and mission of unlocking the community’s progress to ensure that AI, which is the greatest breakthrough of our lifetime, is accessible to as many people as possible,” Chaumond concludes.

See also: Motional and MIT AI explains self-driving car decisions

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