US semiconductor startup Ayar Labs has raised $500 million in a Series E funding round to expand its production capacity and accelerate the deployment of its optical AI infrastructure technology.
The round was led by Neuberger Berman and included participation from global institutional investors such as AKR Invest, Insight Partners, Sequoia Global Equities, and 1789 Capital. From the Middle East, the round also saw participation from the sovereign wealth fund Qatar Investment Authority.
Strategic investors including Alchip Technologies and MediaTek also joined the round. They join existing backers such as Advent Global Opportunities, Boardman Bay Capital Management, IAG Capital Partners, Light Street Capital, Playground Global, AMD Ventures, and NVIDIA.
Founded in 2015 by Mark Wade, Vladimir Stojanovic, Chen Sun, Rajeev Ram, and Milos Popovic, Ayar Labs develops optical interconnect technologies, also known as co-packaged optics (CPO), designed to replace traditional copper-based electrical connections in chips and data centers.
The company’s AI scale-up CPO solution aims to unlock higher performance and efficiency for artificial intelligence infrastructure by replacing bandwidth-limited copper interconnects with optical connectivity. According to the company, this approach can deliver the performance and efficiency improvements required to support next-generation AI workloads.
With the new funding, Ayar Labs plans to scale high-volume production and testing capacity to accelerate the deployment of its CPO solutions. The company also intends to expand global operations, including its new office in Hsinchu, Taiwan, and strengthen partnerships across the semiconductor and AI ecosystem.
“AI infrastructure is hitting a power wall driven by interconnect inefficiency. As bandwidth demands explode, copper becomes the bottleneck—consuming too much power and limiting AI throughput per watt and per dollar,” said Mark Wade, CEO and co-founder of Ayar Labs.
He added that co-packaged optics overcome these barriers by enabling thousands of GPUs to operate as a unified system, improving performance and efficiency for hyperscale AI deployments. The new funding, he noted, will help the company meet the rapidly growing demands of AI infrastructure.
