Siemens has acquired French startup Canopus AI, which specializes in AI and machine learning for chip wafer and mask inspection. Accordingly, the buyout will enable Siemens help semiconductor manufacturers to achieve new levels of precision and efficiency in wafer and mask inspection processes.

Moreover, this acquisition strengthens Siemens’ position in the semiconductor manufacturing ecosystem and expands it chip design and manufacturing digital thread by integrating additional cutting-edge metrology technologies, enhanced with advanced AI capabilities.

Role of Industrial AI in Chipmaking

Recently, the semiconductor industry has underwent increasingly complex manufacturing challenges. This as device geometries continue to shrink and production volumes scale. For that reason, massive metrology has become critical to ensuring quality and yield in advanced semiconductor fabrication.

Siemens has an extensive portfolio that provides chip manufacturers with intelligent inspection and measurement capabilities that drive operational excellence. With its Canopus AI buyout, Siemens will be able to integrate its innovative AI-powered solutions to complement its existing portfolio.

“The acquisition of Canopus AI exemplifies Siemens’ commitment to leveraging industrial AI to solve critical challenges in semiconductor manufacturing,” said Tony Hemmelgarn, president and CEO, Siemens Digital Industry Software.

In addition, Hemmelgarn added, “(With Canopus AI) we are creating a differentiated, end-to-end EDA digital thread that improves the fidelity of printed wafer patterns, accelerates yield ramp and reduces time-to-volume for advanced nodes.”

Founded in 2021 and based in Grenoble, France, Canopus AI is a fast-growing software and AI company for wafer and mask metrology and inspection. Canopus AI is pioneering ‘Metrospection,’ which enhances metrology and inspection workflows with AI. Specifically, its software framework uses AI to help chip designers and manufacturers meet the extreme precision requirements of advanced technology nodes.

06 February 2026