SAN JOSE — Lumilens, a connectivity platform for AI infrastructure, has emerged from stealth, having been founded to solve the growing networking bottlenecks limiting AI scale. In just two years after its founding, the company is commercially shipping its first product into production AI data centers under a multi-billion dollar customer agreement, and announced more than $700 million in new funding co-led by Atreides Management, Bain Capital Ventures, Meritech, Seligman Ventures, and Spark Capital, with participation from Addition, Alkeon, Harbourvest, J.P. Morgan Private Capital, Mayfield, MVP Ventures, Qualcomm Ventures, Peak XV, Redpoint Ventures, Seifdune and other top-tier investors. The financing values the company at $5.51 billion and brings its total capital raised to over $900 million.
The world’s largest technology companies are spending historic sums on AI infrastructure – Citigroup projects the total will cross $2.8 trillion by 2029 – but buying GPUs is no longer the hard part. Connecting them is. Modern AI models are trained and served across hundreds of thousands of processors that must behave as a single computer, and the performance of that computer is now determined as much by the network linking those chips as by the chips themselves.
The challenge is emerging in two critical places inside the AI data center: scale-out and scale-up fabrics. In the scale-out fabric that ties racks and rows of GPUs together, every processor added multiplies the optical transceivers required. A single 400,000 GPU data center requires more than 2.4 million transceivers and more than five million fiber strands from a market already unable to keep pace. McKinsey projects that 800G optical transceiver production could fall 40-60% short of industry demand through 2027, with 1.6T transceiver shortfalls of 30-40% persisting through 2029.
Inside the rack, physics has imposed a ceiling on the scale-up fabric, where GPUs are wired directly to one another over copper connections. At the data rates AI demands, electrical signals survive only about a meter and a half over copper, confining a tightly coupled domain to a single rack and hundreds of GPUs. When a hyperscaler roadmap calls for thousands of GPUs, breaking that ceiling means replacing copper with photonics.
Lumilens was born to address that constraint. In early 2024, the founding team set out to solve the connectivity problems the largest AI clusters foreshadowed – problems a top hyperscaler was already confronting as it sized the clusters its AI roadmap would require. Within two years, Lumilens’ initial scale-out product finished qualification and then started shipping into that hyperscaler’s production AI data centers under a multi-billion-dollar agreement. Lumilens designs and manufactures optical interconnects for both types of networks inside an AI data center – the scale-up network that directly connects GPUs together within a single compute system, and the scale-out fabric that stitches different racks and clusters together.
“The constraint on AI has shifted from how many GPUs you can buy to how many you can connect,” said Ankur Singla, founder and CEO of Lumilens. “Whether they’re training frontier models or serving them to hundreds of millions of users, hyperscalers told us they need the same two things: far more optical capacity for the networks they run today, and a path to directly connecting thousands of GPUs together into a single cluster. We built Lumilens to deliver both – and to manufacture at the volume, quality, and pace this buildout demands.”
Lumilens is the fourth infrastructure company Ankur Singla has founded. His previous two, Contrail Systems and Volterra, were acquired by Juniper Networks and F5, respectively. He is joined by CTO and co-founder Ted Schmidt, who as a Distinguished Engineer at Juniper Networks helped pioneer the company’s silicon photonics and optical integration efforts, building upon Juniper’s 2016 acquisition of silicon photonics innovator Aurrion – giving Lumilens deep technical expertise that has been advancing optical interconnect technology since well before AI turned it into the industry’s current bottleneck.
The Lumilens portfolio spans the full connectivity stack of an AI data center:
- Scale-up silicon and systems (NPO and CPO): near-package and co-packaged optics that bring optical I/O directly to the GPU, enabling thousands of processors — and, on the company’s roadmap, tens of thousands — to operate as a single, tightly coupled domain
- Scale-out pluggable transceivers (800G, 1.6T, and beyond): optical modules that replace copper links across racks and rows, carrying more data at lower power for the largest AI fabrics
Every product is built on LumiCore, the company’s unified technology platform spanning silicon photonics, mixed-signal ICs, electrical-optical interposers, and optical systems, all developed in-house. A single platform across the portfolio lets Lumilens move from design to customer-qualified product in months rather than years, and ensures each product is engineered for high-volume manufacturing from day one.
At Lumilens, manufacturing is treated as a product in its own right. The company has designed a ground-breaking electrical-optical interposer technology that dramatically simplifies photonic chip assembly, along with proprietary manufacturing process recipes, custom robotics, and test automation – scaling capacity through manufacturing partners and its own large-scale facilities. The model gives customers something the optics industry has rarely offered: rapid innovation in performance and density, matched by the ability to scale production just as quickly.
“Over the past several years, the conversation around AI infrastructure has centered on access to compute,” said Umesh Padval, Managing Partner, Seligman Ventures. “Increasingly, the constraint today is shifting to connectivity and how efficiently thousands of GPUs can operate as a single system. We are excited to partner with Ankur Singla, a proven repeat founder who has assembled a world-class team spanning silicon, optics, software, systems, supply chain and manufacturing expertise to address one of the most important challenges in modern data centers. Lumilens’ early hyperscaler adoption and multi-billions in customer commitments just two years after its founding reflect both the scale of the opportunity and the team’s ability to execute.”
“The critical component in scaling AI is shifting from compute to connectivity,” said Gavin Baker, Managing Partner at Atreides Management. “Focusing on that core AI challenge, Lumilens went from its founding to a qualified product deployed inside a hyperscaler’s production data centers within two years, and is building the manufacturing engine to scale with demand while bringing much-needed diversification to AI supply chains. Speed and scale are a formidable combination, and we’re thrilled to lead this round.”
