Limitless Labs Raises $20M for AI in Manufacturing CAD/CAM

Limitless Labs, the developer of an AI platform for computer-aided design and manufacturing in mechanical parts production, has closed a $20 million Series A round. The round was co-led by Dell Technologies Capital and Square Peg, with participation from Grove Ventures, Meron Capital, and Kinetica.

The company, formerly called LimitlessCNC, builds what it calls the first Agentic Physical AI platform for CAD/CAM. Its software works inside existing engineering tools – Siemens NX CAM, Mastercam, and PTC Creo – to automate CNC programming. The idea is to capture the expertise of experienced programmers and scale it across a manufacturer's operations, reducing the time spent on repetitive or complex toolpath design.

The platform runs across cloud, private VPC, and AWS GovCloud environments, with support for ITAR compliance, a requirement for defense-related manufacturing. That positioning could matter as the Pentagon and its contractors push to modernize supply chains and reduce reliance on manual programming.

Limitless Labs was founded in 2024 by David Priev, Assaf Peleg, and Shahaf Finder. The company is headquartered in Tel Aviv and is expanding its U.S. commercial presence. Total funding to date stands at $27.3 million.

The round comes at a time when industrial AI startups are drawing more attention from both venture capital and strategic investors. Dell Technologies Capital's participation signals interest from the hardware and infrastructure side, while Square Peg, an Australian-Israeli fund, has backed a range of deep-tech companies. The involvement of Grove Ventures, Meron Capital, and Kinetica rounds out a syndicate focused on industrial automation.

For manufacturers, the pitch is straightforward: fewer hours spent on CAM programming, faster turnaround on new parts, and less dependency on a shrinking pool of veteran CNC programmers. Whether the platform can deliver on that across the variety of shop-floor environments – from aerospace job shops to high-volume automotive lines – will determine how quickly adoption scales.