Optical systems for AI vision
Optical systems for AI vision
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Two production-oriented platforms, one tuned for image classification, one for object detection.
One optical core. Two vision pipelines. Standard rack integration.
One optical core. Two vision pipelines. Standard rack integration.
Both Lumen and Helio share the same free-space optical core and host stack — so deployment, monitoring, and software updates work the same way across your fleet.
Alvis Lumen - Classification
Alvis Lumen - Classification
High-throughput image classification, computed in light.
Lumen executes the convolutional and dense layers of vision models in the optical domain. Lumen is designed for workloads where billions of images per day need to be tagged, routed, or filtered at the edge of a data center.
Alvis Helio - Object Detection
Alvis Helio - Object Detection
Real-time object detection, optically accelerated.
Helio extends the Alvis optical core with a multi-region detection front-end. Helio is built for the workloads conventional accelerators struggle to feed continuously: high-resolution video analytics, large-scale visual search, and content moderation pipelines where every watt and every millisecond matter.
Drop-in deployment
Standard 19-inch rack units, redundant power, hot-swap modules, and remote management — no exotic infrastructure required.
Familiar software
Export from PyTorch or ONNX. Our compiler maps supported layers onto the optical core and runs the rest on the host CPU/GPU.
Lower TCO
Less power, less heat, less rack space per inference — directly improving the economics of large vision deployments.
Evaluating optical for your data center?
We work with infrastructure teams to scope pilots, benchmark on real workloads, and plan rack-scale rollouts. Reach out and let's talk specifics.
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