Ultrafast photonics for next-generation compute
LightScale Photonics builds ultrafast photonic switching for AI interconnects: faster optical switching, lower communication power, and adaptive network fabrics for the next generation of compute.
AI infrastructure is hitting a communications wall
The bottleneck
Compute scaled. The network didn't. As clusters grow, communication — not raw FLOPs — is the binding systems constraint. Every electronic hop pays an optical-to-electrical-to-optical conversion in power, latency, and cost per bit. A 100,000-GPU cluster needs ~600,000 optical switches: roughly $600M in transceivers and 18 MW of power, just for the network.
What's needed
Future systems need a switching layer that moves more data with less energy and reconfigures on workload time scales. Optical circuit switching has already cut interconnect power by ~40% vs co-packaged optics, 2.6× vs pluggables, and over 10× vs copper. The next step is to push significantly further.
Built for high-speed, low-energy switching
Our platform targets switching speed, energy, and footprint in regimes that conventional approaches struggle to reach.
Ultrafast switching
Push optical switching into a faster operating regime than conventional platforms allow.
No moving parts
A field reroutes the light, not a mirror, a heater, or an injected carrier. Solid-state photonic switching with nothing to wear, warm, or wobble.
Lower switching energy
Energy stored, not burned. Target per-switch energy roughly 1,000× lower than current silicon photonic switches, by replacing heat-driven control with non-thermal switching.
Designed for AI training and inference
AI collectives — all-reduce, all-to-all, MoE routing, bandwidth-heavy inference — want the fabric to reshape on µs-to-ns timescales, inside a single operation. Today's interconnects can't go there. Ours is built for it.
A programmable photonic network layer
The long-term goal is topology on demand: a software-defined photonic fabric that can reconfigure at packet cadence, respond to congestion and link health, and match connectivity to the workload in real time.
AI interconnects first. Broader photonics next
AI infrastructure is the first market. That's where this platform creates the clearest near-term advantage.
Over time, the same platform extends into adjacent domains including photonic compute primitives and quantum photonics.
Introducing Scale1
Our first photonic network switch
Scale1 is LightScale's first photonic network switch, built to turn the platform into a concrete interconnect product for AI infrastructure.
It is the first switch built for Hyperlane, our topology-on-demand network architecture, with a focus on faster data movement, lower communication overhead, and more adaptive connectivity across bandwidth-heavy workloads.
Latency reduction
The switching path is designed to reconfigure at packet cadence, fast enough to change topology within a collective operation, not just between runs. The goal is to make connectivity changes cheap enough to use inside the data path, not as a slow control-plane action layered on top of it.
Hyperlane — topology on demand
Topology, routing, and link assignment are exposed to the control plane. Operators can match fabric shape to workload patterns (training, inference serving, MoE routing) and feed congestion and link-health signals back into reconfiguration decisions in real time.
Non-thermal switching
Scale1 uses a non-thermal photonic switching matrix, integrated at the device level rather than assembled from discrete optical components. It is designed to scale switch radix without the thermal load or per-port power overhead of conventional reconfigurable optics.
In development: Photon1
A photonic compute chip
Designed for AI training and inference with efficiency at scale.
Photon1 targets matrix math in the optical domain — unitary operations performed by interference, with all-optical activation, so the inner loop never leaves the photonic domain.
Built on the same platform as Scale1, and programmed through the same LUMA software stack.
The software: LUMA
One programming model across photonic switching and compute
LUMA — the Light Unified Matrix Architecture — is the software layer above LightScale's photonic hardware. A single API spans the Scale1 switching fabric and Photon1 compute: developers write to LUMA, not to individual devices.
Topology, routing, and link assignment are exposed to software and reconfigured at packet cadence. The same code targets every generation, from Scale1 onward, with no per-device rewrite.
Built on demonstrated photonics
Built on layered 2D semiconductor photonics, backed by published research and an active patent program, with a roadmap toward manufacturable photonic switching hardware.
Core functionality validated
Published work shows the platform's core photonic behavior in lab environments.
Process maturity
Key fabrication steps have already been demonstrated in the lab.
IP in progress
Patents have been submitted across the core architecture.
Built by researchers at the intersection of photonics and computing
LightScale brings together expertise across photonics, materials, fabrication, large-scale systems, AI infrastructure, and quantum computing, with backgrounds at MIT, Harvard, University of Toronto, Broadcom, NVIDIA, Google, IBM, and Amazon.
Leadership
Kabir Swain
Founder & CEO
John P.
Chief Scientific Officer
Sijie Han
Chief Operating Officer
Manel Baradad
Chief Technology Officer
Tracey Ooi
Chief Financial Officer
Advisors
David Garrett
Advisory Board Member
Daniel Karl I. Weidele
Advisory Board Member
The future of compute needs a new interconnect layer
We're building it: ultrafast, low-energy, programmable photonics, starting with Scale1.