Key Takeaways
- • Oxford-based Salience Labs raised an oversubscribed $125 million Series B led by Bullhound Capital to scale its all-optical circuit switching technology for AI data centers.
- • New investors Intel Capital, AMD Ventures, SBI Group, Hudson River Trading and the British Business Bank joined existing backers including Applied Ventures, Oxford Science Enterprises, Cambridge Innovation Capital and Silicon Catalyst Ventures.
- • Salience demonstrated what it describes as the world's first 64-port all-optical photonic switch at ECOC 2026 in September, with 128-port and 256-port configurations under development.
- • Citing Cignal AI, the company projects the optical circuit switching market will exceed $8 billion by the end of the decade.
Summary
Oxford-based Salience Labs has raised an oversubscribed $125 million Series B led by Bullhound Capital, according to HedgeCo.Net. Intel Capital, AMD Ventures, SBI Group, Hudson River Trading and the British Business Bank joined as new investors, while existing backers Applied Ventures, Oxford Science Enterprises, Cambridge Innovation Capital and Silicon Catalyst Ventures also participated.
The company targets a bottleneck that has become central to AI infrastructure economics. Most data centers still rely on electronic switches and repeated optical-to-electrical-to-optical conversions, which co-founder and chief executive Vaysh Kewada argues cannot keep pace with the throughput demands of clusters built from tens of thousands of accelerators. Salience has developed an integrated, silicon photonics-based switch architecture designed to route data optically, reducing latency and power consumption.
At the ECOC 2026 conference in September, Salience demonstrated what it described as the world's first 64-port all-optical photonic switch and said denser 128-port and 256-port configurations are in development. The company cited Cignal AI forecasts that the optical circuit switching market will exceed $8 billion by the end of the decade. Proceeds will fund volume manufacturing, geographic expansion and research on higher-density switches.
The investor base carries strategic significance. Participation from the venture arms of two leading chipmakers, Intel Capital and AMD Ventures, suggests incumbents view optical switching as complementary to their roadmaps. Hudson River Trading, a quantitative trading firm whose business depends on low-latency networking, also joined the round.
For venture investors, the round reflects capital moving down the AI stack from models and applications toward networking, power and interconnect, where efficiency gains translate directly into the cost of running large workloads.
The company targets a bottleneck that has become central to AI infrastructure economics. Most data centers still rely on electronic switches and repeated optical-to-electrical-to-optical conversions, which co-founder and chief executive Vaysh Kewada argues cannot keep pace with the throughput demands of clusters built from tens of thousands of accelerators. Salience has developed an integrated, silicon photonics-based switch architecture designed to route data optically, reducing latency and power consumption.
At the ECOC 2026 conference in September, Salience demonstrated what it described as the world's first 64-port all-optical photonic switch and said denser 128-port and 256-port configurations are in development. The company cited Cignal AI forecasts that the optical circuit switching market will exceed $8 billion by the end of the decade. Proceeds will fund volume manufacturing, geographic expansion and research on higher-density switches.
The investor base carries strategic significance. Participation from the venture arms of two leading chipmakers, Intel Capital and AMD Ventures, suggests incumbents view optical switching as complementary to their roadmaps. Hudson River Trading, a quantitative trading firm whose business depends on low-latency networking, also joined the round.
For venture investors, the round reflects capital moving down the AI stack from models and applications toward networking, power and interconnect, where efficiency gains translate directly into the cost of running large workloads.
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