San Francisco-based semiconductor startup Volantis on Thursday said it has raised $88 million in venture capital in an effort to solve a key challenge for AI chips by tapping a technology that is...

Volantis raises $88M Series A to advance photonic memory architecture. October 1, 2026 Press play to listen to this content New photonic architecture will power AI inference for models exceeding 20 trillion parameters at up to 10,000 tokens per second per user SAN FRANCISCO, Oct. 1, 2026 - Volantis, a semiconductor company building a new category of AI inference system, today announced an $88 million Series A co-led by Lachy Groom and Abstract Ventures, with participation from John Doerr, VXI Capital, Triatomic and Susa Ventures. The round also includes angel investors Dwarkesh Patel, Naveen Rao and Sholto Douglas. Volantis is building a new AI inference architecture that eliminates the tradeoff between memory capacity and bandwidth. Its first system, A-1, is being designed to run models exceeding 20 trillion parameters at up to 10,000 tokens per second per user, while reducing inference cost per token. The company's founding team includes semiconductor and photonics veterans from NVIDIA, AMD, Broadcom and Ayar Labs. Their previous work includes the first CoWoS product, the first high-volume tunable VCSELs and early silicon photonics co-packaged optics systems. "As AI agents take on more work, how fast they complete that work will increasingly determine how fast companies can operate," said Tapa Ghosh, CEO and co-founder of Volantis. "Today's hardware forces a tradeoff between running the largest, most sophisticated models and running them fast. We started Volantis to eliminate that tradeoff." Breaking Through the AI Memory Wall Running large AI models at high speeds requires enormous memory capacity to hold the model and enormous bandwidth to continuously feed data into the compute engine. Existing architectures force a compromise between the two. On-chip SRAM provides high bandwidth but limited capacity, constraining model size and context windows while increasing cost and energy consumption. GPUs and other HBM-based systems provide greater capacity, but bandwidth limits how quickly they can serve increasingly large models. Even newer approaches such as 3D DRAM remain on the same tradeoff curve. Volantis is designing A-1 to increase memory capacity and bandwidth simultaneously by nearly two orders of magnitude, allowing increasingly large models to run at much higher inference speeds. That performance could significantly accelerate AI agent workflows. A coding agent that completes a task in two minutes instead of 30 gives developers more opportunities to test ideas, ship software and iterate. As agents take on longer and more complex work, inference speed increasingly determines how quickly they can complete it. A New Approach to Photonic Interconnects Volantis is building a new category of photonic interconnect designed specifically to connect compute chips to memory. Its optical fabric connects large numbers of memory chips into a unified pool, aggregating their bandwidth as memory is added. This allows A-1 to increase memory capacity and bandwidth together while using lower-cost off-chip memory. While photonics is already used to move data inside data centers, existing technologies have largely focused on chip-to-chip connections. Chip-to-memory connections require more than 100 times as much data to travel over much shorter distances, creating different requirements for energy and cost. Volantis developed a photonic platform specifically for this environment. Its architecture uses custom micro-VCSELs rather than external lasers, drawing on the existing gallium arsenide VCSEL supply chain and avoiding indium phosphide supply constraints. The micro-VCSELs are small, temperature-stable and low power, enabling end-to-end links consuming less than one picojoule per bit. Volantis plans to unveil additional innovations behind the architecture as A-1 moves toward commercialization. Investment and Commercialization Volantis plans to deliver its first integrated inference engines to customers in 2027. The financing will support the development and commercialization of A-1 and its photonic memory architecture, including expanding the company's engineering team and moving the system toward customer deployments. About Volantis Volantis is a semiconductor company building a new architecture for AI inference. The company combines photonics and semiconductor design to increase memory capacity and bandwidth, enabling larger AI models to run at significantly higher speeds. For more information, visit https://volantissemi.ai. Neoclouds are spending a fortune on GPUs, and they need to keep those GPUs doing... 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