The Pulse
Circuit Mind Raises $25M and Launches AI Design Verification
Circuit Mind disclosed $25 million in financing, including an $18.5 million Series A led by Norwest, and launched its Agentic Verification Engine. The London company says the software checks circuit designs against component datasheets and
AI.info Team · Written with AI · fact-checked ·
Circuit Mind is pitching AI for an engineering process where a nearly correct design can still mean months of delay. The London company says general-purpose language models lack the circuit knowledge and customer-specific rules needed for reliable electronics work; its answer is software that combines AI agents with physics-based checks. On October 28, it announced $25 million in financing and launched a tool designed to catch schematic issues before a prototype is built.
“Software teams are shipping 100 times faster with AI, but electronics design hasn't changed in 40 years,” said Tomide Adesanmi, Circuit Mind’s co-founder and CEO. The company’s announcement pairs that claim with a new verification product, but its customer results so far are company-reported rather than independent benchmarks.
AVE checks schematics against parts data
The new product, AVE (Agentic Verification Engine), uses AI agents to check designs against component datasheets and an organization’s own design rules. Circuit Mind says the checks can surface issues that conventional schematic reviews may miss, before a board reaches prototype manufacturing. The release does not provide a separate accuracy rate or quantified performance result for AVE.
AVE joins Circuit Mind’s existing ACE (Assistant to Circuit Engineers), which turns a hardware block diagram into a schematic, bill of materials and supporting analysis. The company says ACE can generate options tuned for cost, size, power or supply availability. Its platform combines agentic AI, structured machine-readable component models, customer engineering context and what Circuit Mind describes as a patented, physics-based decision engine.
The software is designed to work with electronic computer-aided design tools, component libraries, product-lifecycle management systems and other engineering environments teams already use. Circuit Mind says customer context can include approved manufacturers, preferred parts and design rules—constraints that generic models may not know.
Norwest leads an $18.5M Series A
The $25 million financing package includes an $18.5 million Series A led by Norwest, alongside a seed round Circuit Mind had not previously disclosed. Existing investors Third Prime, Differential and Blackhorn joined the Series A, as did new investor Lightscape VC. Circuit Mind said its total funding now stands at $33.4 million.
Dave Zilberman, a general partner at Norwest, will join the company’s board. Circuit Mind plans to use the financing to extend its platform across more stages of electronics design, expand its sales, engineering and customer-success teams, and establish a U.S. headquarters to serve the North American market.
Company cites customer gains, with limits
Circuit Mind says engineering teams at Emerson, Schneider Electric and Fortune 5 companies are using its platform. The company reports that customers have cut design work from months to weeks, reduced bill-of-materials costs by 25% and avoided manufacturing respins that can add more than a month to schedules. The announcement does not identify the Fortune 5 customers or provide a breakdown of the measurements behind those figures.
Schneider Electric’s Daniel Gheno, SVP of Innovation and Technology and CTO of Energy Management, said early evaluations show the potential to reduce architecture-exploration effort by more than 90%. That figure refers to exploration effort, not a measured reduction in the full electronics-design timeline. Circuit Mind also cites a peer-reviewed case study in which engineers at Los Alamos National Laboratory completed a design in four hours that the company says would otherwise have taken two weeks.
The financing and AVE launch put Circuit Mind’s central proposition in sharper focus: use AI to speed up design, but anchor its choices in electrical constraints and each customer’s rules. Whether AVE finds errors that existing review misses at a dependable rate is a separate question; the launch announcement gives no AVE-specific benchmark.