Volantis has raised $88 million in Series A funding to develop and commercialize a new photonic architecture designed to address memory capacity and bandwidth constraints in AI inference systems. The round was co-led by Lachy Groom and Abstract Ventures, with participation from John Doerr, VXI Capital, Triatomic and Susa Ventures. Angel investors Dwarkesh Patel, Naveen Rao and Sholto Douglas also participated.
Volantis is developing an AI inference architecture designed to increase memory capacity and bandwidth simultaneously rather than requiring systems to trade one against the other.
Its first system, A-1, is being designed to run AI models exceeding 20 trillion parameters at speeds of up to 10,000 tokens per second per user while reducing inference cost per token.
The founding team includes semiconductor and photonics veterans from NVIDIA, AMD, Broadcom and Ayar Labs. Their previous work includes the first CoWoS product, high-volume tunable VCSELs and early silicon-photonics co-packaged optical systems.
Volantis is targeting what the company describes as the AI memory wall. Running increasingly large models requires both enough memory capacity to hold model parameters and sufficient bandwidth to continuously feed those parameters into compute engines.
On-chip SRAM provides high bandwidth but limited capacity, while HBM-based GPU systems offer greater capacity but can become constrained by bandwidth as model size increases.
Volantis said A-1 is being designed to increase memory capacity and bandwidth by nearly two orders of magnitude simultaneously.
The company is developing a photonic interconnect specifically for connections between compute chips and memory. Its optical fabric connects large numbers of memory chips into a unified pool and aggregates bandwidth as additional memory is added.
Volantis’ architecture uses custom micro-VCSELs instead of external lasers and draws on the existing gallium arsenide VCSEL supply chain. The company said its micro-VCSELs enable end-to-end links consuming less than one picojoule per bit.
The company plans to deliver its first integrated inference engines to customers in 2027.
Proceeds from the Series A will support development and commercialization of A-1 and its photonic memory architecture, expansion of the engineering organization and preparations for customer deployments.
KEY QUOTES:
“As AI agents take on more work, how fast they complete that work will increasingly determine how fast companies can operate. Today’s hardware forces a tradeoff between running the largest, most sophisticated models and running them fast. We started Volantis to eliminate that tradeoff.”
Tapa Ghosh, CEO and Co-Founder of Volantis
