Liquid Instruments lands $50M to scale AI test platform
Liquid Instruments Pty. Ltd. raised $50 million in Series C funding to expand its software-defined test and measurement platform, with particular focus on aerospace, defense and semiconductor applications.
The round was co-led by Keysight Technologies and Australia's National Reconstruction Fund Corporation. Keysight is also entering a commercial partnership with Liquid Instruments for joint development of AI-driven instrumentation.
What the company does
Liquid Instruments, founded in 2014 with offices in San Diego and Canberra, builds reconfigurable hardware that replaces traditional racks of separate test instruments with a single software-defined device. Its main product, Moku, uses field-programmable gate arrays with a software layer that lets users change the hardware's function without physical reconfiguration.
The approach reduces costs on dedicated instruments, saves lab bench space, and allows engineers to write custom digital signal processing for applications where off-the-shelf tools don't fit the need.
Who uses it
Liquid Instruments serves thousands of users across technology companies, research institutes, quantum startups and defense contractors. Customers include national laboratories, university physics departments, and electronics manufacturers using the hardware in production test environments.
The flexibility proves especially valuable in quantum research, where experimental designs change faster than vendors can update product catalogs.
The funding context
This round brings Liquid Instruments' total funding to more than $100 million. The National Reconstruction Fund Corporation's participation reflects the Australian government's effort to support domestic capability in critical technology sectors.
Co-founder and CEO Daniel Shaddock said the Keysight investment validates the company's approach. "As systems grow more complex, our users need more flexible, AI-driven tools, and this new partnership with Keysight will accelerate that shift," he said.
For product development teams evaluating test infrastructure or working with complex measurement systems, AI for Product Development covers how AI is reshaping engineering workflows. Those in research environments may find AI for Science & Research directly applicable to laboratory optimization and data analysis challenges.
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