Freeform Raises $67 Million to Apply Generative AI to Manufacturing Process Optimization
Freeform closes a $67 million Series B to scale its generative AI platform that optimizes manufacturing processes — using machine learning to predict defects, adjust parameters in real time, and reduce material waste across additive and subtractive manufacturing workflows.
Freeform has closed a $67 million Series B to scale its generative AI platform that optimizes manufacturing processes — using machine learning to predict defects, adjust parameters in real time, and reduce material waste across additive and subtractive manufacturing workflows.
AI in Manufacturing
Freeform's platform sits between the design file and the manufacturing machine, using AI to optimize the parameters that control the manufacturing process. For 3D printing (additive manufacturing), this includes laser power, scan speed, layer thickness, and support structure placement. For CNC machining (subtractive manufacturing), it includes tool path optimization, cutting speeds, and coolant flow. By continuously monitoring the manufacturing process through sensor data and adjusting parameters in real time, the platform reduces defect rates and material waste while increasing throughput.
Closed-Loop Optimization
The key technical innovation is closed-loop optimization: the AI system observes the results of each manufacturing step (through cameras, thermal sensors, and dimensional measurements), compares the results to the intended outcome, and adjusts subsequent steps accordingly. This is particularly valuable in metal 3D printing, where thermal management is critical and small variations in temperature can cause microstructural defects that compromise part integrity. Freeform's closed-loop system detects and corrects for these variations in real time.
Market Opportunity
The manufacturing AI market is projected to exceed $20 billion by 2028, driven by demand for higher quality, lower waste, and faster production cycles. Freeform's customers include aerospace and defense manufacturers who require the highest quality standards and are willing to invest in AI optimization to reduce the scrap rates that currently make advanced manufacturing expensive. The Series B funding will be used to expand the platform's support for additional manufacturing processes and to scale the sales team for enterprise deployment.
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