Photonic Switching Developer Backed by Applied Ventures and ICM HPQC Fund
Salience Lab's technology uses a broad bandwidth of light to create a high-speed, ultra-low latency multi-chip processor that removes the bottlenecks in the AI network
Salience Labs develops photonic switching technology, which uses light instead of electrical signals to transfer data, enabling higher bandwidth, lower latency, and reduced power consumption. This technology is particularly beneficial for AI data centers, and high-performance computing (HPC) facilities.
Salience Labs, an Oxford-based leader in photonic solutions for AI data center connectivity, has successfully closed a $30 million Series A financing round.
The new round was led by Applied Ventures and ICM HPQC Fund, the venture capital arm of Applied Materials, Inc. Other participants in this round included Braavos, Oxford Sciences Enterprises, Cambridge Innovation Capital, Silicon Catalyst, and Jalal Bagherli.
Salience Labs develops photonic switching technology, which uses light instead of electrical signals to transfer data, enabling higher bandwidth, lower latency, and reduced power consumption. This technology is particularly beneficial for AI data centers, high-performance computing (HPC) facilities, and semiconductor companies that require scalable and energy-efficient network architectures. By leveraging silicon photonics, which integrates optical and electronic components on a single chip, Salience Labs aims to improve AI cluster performance and efficiency. The company’s research is based on work conducted at the University of Oxford and the University of Münster.
Salience Labs was co-founded in 2021 by CEO Vaysh Kewada and is headquartered in Oxford, England, with plans to expand into the United States.
Vaysh Kewada
“What our customers want is a photonic switch to connect their AI clusters that is compatible with existing infrastructure while delivering high bandwidth, low latency, and significant power savings. The completion of this round will further our development and help us bring our product to customers to enable not just the savings, but large cluster connectivity,” said Ms. Kewada. “We are also excited to be working closely with our strategic investors who are industry leaders to advance our go-to-market schedule.”
“Silicon photonics is a promising technology to deliver significant advancements in energy-efficient performance for AI data centers,” said Anand Kamannavar, Vice President and Global Head of Applied Ventures. “Salience’s optical switch solution has the potential to enable a new generation of interconnect network architectures for faster and more efficient AI systems.”
Simultaneously with this funding round, Salience Labs has hired Bonnie Tomei as the company’s chief financial officer. Ms. Tomei is a certified public accountant and a Silicon Valley industry veteran with over 20 years of experience, including IPOs and de-SPAC transactions.
Bonnie Tomei
“With over 20 years of experience, including initial public offerings, de-SPAC, and a strong business operations background, Ms. Tomei will be a key member of the executive team to realize our strategic and operational objectives, including expanding to the U.S. to serve our key customers,” said Ms. Kewada.
Applied Ventures, based in California, is the venture capital arm of Applied Materials, a major semiconductor and materials engineering company. The firm invests in early- to growth-stage companies working on semiconductors, AI hardware, advanced materials, photonics, and quantum computing. Applied Ventures typically backs companies that complement Applied Materials’ technology portfolio, with a focus on manufacturing innovation, computing efficiency, and next-generation materials. The firm has made investments in startups across North America, Europe, and Asia.
ICM HPQC Fund, headquartered in Singapore, is an investment fund focused on high-performance quantum computing (HPQC) and advanced computing technologies. The fund primarily invests in companies developing photonics, AI hardware, and quantum computing solutions that aim to improve computational efficiency and scalability.