CloudNC Raises $20 Million to Speed Up AI Automation in Manufacturing
CloudNC has secured $20 million in a Series B extension to advance its AI tools for precision manufacturing.
The round brings the UK company's total capital raised to $128 million and was led by Nimble Ventures, with participation from Calculus Venture Capital, Entrepreneur First, and LM Ventures, Lockheed Martin's venture arm.
Why Manufacturing Bottlenecks Matter Today
Founded in 2015, CloudNC focuses on automating complex decisions in CNC machining that can slow down production.
Its software, called CAM Assist, works alongside existing computer-aided manufacturing systems to generate machining strategies and toolpaths more efficiently, helping machinists move from design to production faster.
More than 1,000 machine shops worldwide already use CAM Assist, with several hundred of them in the United States. The software leaves machinists in control, allowing them to review, approve, and adjust its output.
This approach keeps human experts involved while handling repetitive programming and planning work that can otherwise take skilled machinists hours to complete.
How AI Could Reshape Factory Jobs and Supply Chains
The new funding will support CloudNC's commercial expansion into existing and new markets, further development of its product line, and the rollout of Quote Agent, a new AI tool designed to help manufacturers assess jobs and respond to customer inquiries more quickly.
Factories face growing pressure from labor shortages and efforts to bring more manufacturing back home, increasing demand for tools that can help existing workers and machines produce more efficiently.
Smaller shops may gain an edge by quoting faster and using their machines more effectively.
Over time, this technology could contribute to quicker production and delivery of components used across industries such as automotive, defense, and consumer hardware.
Long-term success depends on proving the software can address more manufacturing bottlenecks and expand effectively across existing and new markets.
The effort highlights how targeted AI can address real factory challenges while keeping skilled workers involved in the manufacturing process rather than replacing human expertise entirely.
