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Hyphastructure Debuts Edge Cloud Network for Physical AI

Hyphastructure launches a distributed Edge Cloud Network for physical AI, delivering sub-10ms latency to power real-time robotics, smart cities, and edge computing.

Written By
thumbnail Jordan Smith
Jordan Smith
Oct 16, 2025
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Hyphastructure, an edge cloud company purpose-built for AI inference, has launched a distributed Edge Cloud Network purpose-built for physical AI, redefining the possibilities of ultra-low-latency, high-performance computing at the edge.

Platform promises sub-10 millisecond latency for AI inference

The new platform places data center-grade infrastructure at the physical edge where data is generated and delivers AI inference latency under 10 milliseconds across a network of distributed local nodes.

The latency under 10 milliseconds unlocks real-time applications across industries, including autonomous robotics, vehicle-to-vehicle (V2V) collision avoidance, and smart city infrastructure.

“Hyphastructure delivers the infrastructure layer AI-powered industries have been waiting for,” said Michael Huerta, CEO of Hyphastructure. “By moving inference to the edge, we’re removing latency barriers and opening the door to transformative applications from tele-surgery to robotics that were impossible before.”

Intel accelerators, networking, and virtualization combine at the edge

Hypastructure’s unified edge platform will integrate Intel Gaudi 3 AI accelerators, software-defined networking, and bare-metal virtualization. This will give enterprises agility in deploying and managing complex AI models at the edge.

Customers can expect to see a number of benefits from this platform, including:

  • Quicker AI deployment: Enterprises can move from model development to real-world deployment in hours and not weeks with a fully integrated stack.
  • Lower total cost of ownership (TCO): Intel Gaudi 3-based infrastructure offers up to 40 percent lower TCO compared to traditional GPU-based systems, as validated by independent benchmarks.
  • Seamless orchestration at scale: The platform’s software-defined networking and virtualization allow for dynamic scaling and management of AI workloads across distributed nodes without sacrificing performance.
  • Real-time decision making: By processing data locally at the edge, the Hyphastructure network eliminates the latency and bandwidth constraints of centralized cloud systems, enabling real-time insights and actions.

According to Hyphastructure, the organization supports use cases across various industries, including:

  • Smart cities: Delivering the first edge-based architecture capable of coordinating traffic, crime, and emergency services across urban areas.
  • Smart retail: Enabling real-time shelf monitoring and personalized offers at the edge without relying on on-premises resources.
  • Autonomous systems and robotics: Providing the first decentralized platform for supporting collision-avoidance inference through V2V networks– a capability for next-gen vehicles, robotics, and drones.
  • Gaming and interactive media: Powering the first sub-10 millisecond edge compute service and powering immersive AR/VR experiences that cannot tolerate the latency of centralized cloud systems.

As more organizations seek to utilize AI in their software and hardware, strategic deployment becomes even more crucial. Learn more about how Coralogix is enabling agentic AI deployment with its MCP server.

thumbnail Jordan Smith

Jordan Smith is a news writer who has seven years of experience as a journalist, copywriter, podcaster, and copyeditor. He has worked with both written and audio media formats, contributing to IT publications such as MeriTalk, HCLTech, and Channel Insider, and participating in podcasts and panel moderation for IT events.

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