Cognichip raised $60M to train AI to design chips for AI

Startup Cognichip raised $60 million to develop technology that uses artificial intelligence to design the chips themselves—the very ones that modern AI cannot exist without. The company claims that its approach will reduce semiconductor development costs by more than 75% and timelines by more than half. These are radical figures for an industry where creating a new chip traditionally takes years and costs billions of dollars.

Nvidia, Apple, Google and other players spend enormous resources on designing, verifying, and testing each new generation of processors. Cognichip wants to automate a significant portion of this process using AI agents capable of making architectural decisions, optimizing circuits, and reducing the number of iterations between engineering teams. Essentially, it's about creating an AI copilot for chip designers—or, in a more ambitious scenario, fully automating certain stages of development.

The startup is entering a rapidly growing segment of EDA (Electronic Design Automation)—tools for automating electronics design. Traditional market players such as Synopsys and Cadence are already embedding machine learning elements into their platforms, but Cognichip is betting on a native AI approach from the ground up rather than an overlay on legacy systems. The closure of this feedback loop is remarkable: the shortage of computing power for training AI models is directly connected to how quickly the industry can design new chips.

If Cognichip delivers on its promises, it will accelerate not only hardware production—but also the development of the AI itself that consumes this hardware. Similar claims about radical cost reduction in the semiconductor industry are made regularly, and the startup still has a long way to go before achieving commercial results. Nevertheless, the $60 million round signals serious investor interest in the idea of closing the loop: using AI to create the infrastructure on which AI runs.