Piris Labs

Founded by Ali Khalatpour in 2025

Connect AI compute and memory using optical networking hardware and execution

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You can use Piris Labs to interconnect AI computing systems and memory using optical hardware and execution software. The system replaces standard electrical connections with nanoscale photonics, including frequency comb lasers and high-bandwidth optical links. It also provides optical PCIe interconnects tailored for CXL devices to reduce latency and power consumption across AI clusters. Teams can route stateful multi-step AI workloads across distributed infrastructure to keep data movement fast and cost-effective across large-scale training and inference setups.

What Piris Labs does

Connect compute nodes to pooled memory over optical PCIe linksDistribute shared multi-wavelength laser sources across server racksRoute inference requests dynamically to meet workload latency targetsMeasure RF and photonic signal loss across high-speed optical channelsDeploy low-latency optical links between training acceleratorsAllocate infrastructure dynamically based on real-time traffic patternsDirect electro-optic conversion architecture converting electrical signals to lightHigh-bandwidth Iris optical links for scale-up AI interconnectsHermes optical PCIe interconnect engineered for CXL connectivityFrequency comb laser acting as a shared multi-wavelength light sourceAI Endpoint execution software for routing stateful multi-step workloadsDynamic infrastructure allocation based on real-time traffic patterns and latency targetsCustom nanoscale photonic fabrication designed for cleanroom testing

Pricing breakdown

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Tutorials & Demos

Frequently asked

PyTorch, TensorFlow, Hugging Face, Kubernetes, Docker, REST API, Python SDK, Unverified, PCIe, CXL, NVIDIA, PyTorch: Standard deep learning framework support, Hugging Face: Model repository integration, TensorFlow: Machine learning library compatibility, Unverified: Kubernetes orchestration, Unverified: Python SDK for inference, Unverified: REST API for model serving, NVIDIA GPU Clusters, CXL Devices, NVIDIA Inception Program, Cloud Infrastructure APIs, Forensic Analysis Suites, Custom Webhooks, Distributed Compute Fabrics, Custom API and Webhooks, Hyperscale data center fabrics, SBIR Government partnerships, NVIDIA GPU clusters (as interconnect), Proprietary execution software, REST API (Inference endpoints), Webhooks (Event notifications), NVIDIA Inception Program (Ecosystem), Optical Networking Hardware (Proprietary), Cloud Storage (Data scanning), Unverified (Standard MLOps tools), Unverified (CI/CD pipelines)

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