Salience Labs, a UK-based developer of photonic solutions for AI datacentre infrastructure, has closed a $30m in Series A funding round.
The investment was led by ICM HPQC Fund and Applied Ventures, the venture capital arm of Applied Materials.
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Other investors include Strategic Investment Fund, Braavos, and existing backers such as Oxford Sciences Enterprises, Silicon Catalyst, Cambridge Innovation Capital, and semiconductor industry veteran Jalal Bagherli.
Salience Labs co-founder and CEO Vaysh Kewada said: “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.”
Salience Labs plans to use the proceeds to further advance the development of its optical switch technology, designed to enhance connectivity within large-scale AI infrastructure.
Applied Ventures global head and vice-president Anand Kamannavar said: “Salience’s optical switch solution has the potential to enable a new generation of interconnect network architectures for faster and more efficient AI systems.”
Alongside the financing announcement, Salience Labs has announced key leadership appointments.
Dr Jeffrey joins the company’s board of directors, bringing experience from roles at the National Institute of Standards and Technology and SRI International.
He will serve alongside Jack Edmondson, chief investment officer of Oxford Sciences Enterprises, and Daniel Armbrust, co-founder of Silicon Catalyst.
The company has also appointed Bonnie Tomei as its new CFO.
Kewada said: “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 realise our strategic and operational objectives, including expanding to the US to serve our key customers.”
Founded in 2021, Salience Labs leverages research from the University of Oxford and the University of Münster to develop photonic switching technologies.
These technologies aim to provide high-speed, ultra-low latency networking for AI applications, addressing infrastructure challenges in the rapidly evolving field.
