The company develops explainable/interpretable AI and ML solutions for IC design workflow that deliver faster time to market, better quality, and accelerated yield ramps. With the latest financing, which was led by Intel Capital, the company says that it is set to take significant strides to deliver on its vision of using its AI-driven solutions to reduce by a factor of 10 today’s time and cost to design and ramp yield on the next generation of chips.
The company says that it plans to apply the funding to scale the business and double the team within the next 12 months.
“The Motivo team has combined decades of expertise in IC design, computational imaging and manufacturing technologies, and artificial intelligence to create solutions that reduce design time to market and accelerate yield ramps for new chips,” says Bharath Rangarajan, CEO of Motivo. “Our customers are faced with increasing challenges as they create their new designs, and the demand for our solutions is so much that we have had to turn away multiple business opportunities. This new investment and support will enable us to rapidly scale up and implement Motivo’s solutions more broadly, deliver value to our customers, and significantly grow our business.”
Creating the next generation of chips, says the company, is a time intensive and expensive process with multiple iterations of trial and error needed to fix design bugs and improve yield. As a result, the traditional chip design and manufacturing process can take years to deliver a chip to market. And with chip design complexity growing exponentially, design cycles are getting longer and yield is getting worse. The company estimates that yield losses will exceed $20 billion in 2025.
Motivo’s technologies accelerate chip design by utilizing an innovative learning-on-graph methodology for automated data-driven feature extraction. The company's technology suite includes M-Graph and other proprietary combinatorial analytics, search, and learning on graph for automated data-driven machine learning feature extraction. The