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Nvidia venture arm backs $67m series B in US manufacturing startup
Freeform, a manufacturing technology company based in California, has announced the closing of US$67 million Series B funding round led by investors including NVIDIA’s venture arm, Two Sigma Ventures, and Founders Fund.
The funding aims to support the development of Skyfall, a next-generation factory platform scheduled to launch in the first half of 2026, which will expand manufacturing capacity and material options.
The company claims its proprietary technology integrates robotics, sensing, simulation, and machine learning into AI-native factories, aiming to make manufacturing more flexible and scalable.
Freeform says its approach seeks to address the gap between rapid human ideation and slower physical production.
The company plans to offer a turnkey service that transforms customer ideas into production-ready products and is hiring in Hawthorne, California, to support its growth.
🔗 Source: Freeform
🧠 Food for thought
Implications, context, and why it matters.
“Physical AI” is one label for the trend behind Freeform’s “AI-native” factories
- “AI-native factories” fits within a broader category called “Physical AI,” a strategy for advanced automation in e-commerce, logistics, and warehouse material handling 1.
- Freeform’s $67 million Series B funding sits within a wider push to put AI into machines, with robotics firm RobCo reported to have raised $100 million 2 and Roark Aerospace reported to have secured $210 million 3.
- NVIDIA’s investment looks planned. Reports have linked NVIDIA to “Physical AI” work in biomanufacturing (using biological systems to make products at industrial scale) and robotics 4, and Freeform explains “Why Nvidia Invested” on its website 5.
Moving AI from screens to factory floors creates new risks and opportunities
- Adding AI to physical systems like factory robots brings real-world constraints that do not come up in software-only products.
- When models such as LLMs steer robots and drones, safety concerns rise. Extra steps are needed to prevent accidents and reduce bias in robots and drones 6.
- “Physical AI” now reaches past specialized manufacturing. Examples include infrastructure drones for aerial construction 7 plus automation for logistics and warehouse material handling 1.
- This shift has pushed incumbents to respond. A post about Roark Aerospace says aerospace players like Airbus have begun looking beyond today’s computers 3.
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