Meet our core partner stack.
Edgescale sits at the center of a powerful partner ecosystem, providing the distributed Physical AI Infrastructure that delivers these best-in-class layers as one integrated system, ready to bring AI to your hard-to-reach data, wherever your physical work happens.
Secure Operating System
Our ecosystem's operating foundation.
Physical AI workloads don’t get to pick their environment – they run in factories, substations, rail yards, and remote sites where the hardware is constrained and the operational bar is high. Red Hat Enterprise Linux, OpenShift, and MicroShift give us a consistent, Kubernetes-based runtime that behaves the same in a data center as it does on an Edgescale Cube at the edge. That consistency is what lets customers manage thousands of distributed sites the way they’d manage a single cloud region, without rewriting their stack for every location.
Compute
Supplying the compute and physical AI models.
Jetson Thor and the broader Jetson family are purpose-built for real-time inference on robots, vehicles, cameras, and industrial machines, and NVIDIA’s software stack – from CUDA to Isaac to Cosmos – is where most of the vision, robotics, and multimodal models our customers want to deploy are built and optimized. Our infrastructure gives those models a managed, production-grade environment to run in, wherever the asset happens to be. Together, NVIDIA and Edgescale bring AI compute directly to the hard-to-reach data powering the physical world.
Operational Data
The decision layer.
Foundry’s Ontology turns messy operational data – equipment, sensors, work orders, crews, inventory – into a live digital model of the business, and AIP lets teams build AI agents and workflows on top of it. Through the Palantir & Edgescale Live Edge partnership, we extend Palantir’s software into the physical environments where the data actually lives, so the Ontology stays hydrated with real-time operational signals and the agents built on it can close the loop back to control systems.
Operational Data
Moving your data where it needs to go.
Physical AI only works if events from machines, sensors, and control systems get to the right model, agent, or operator in time to matter, and Kafka is the de facto standard for enterprise workloads. Confluent gives our ecosystem a real-time data backbone that connects edge sites to the Ontology, to cloud analytics, and to each other, with the governance and replay guarantees that industrial operators require. When an agent needs fresh context to act, or a fleet needs to coordinate across sites, Confluent is the nervous system carrying the signal and Edgescale is the Physical AI Infrastrcuture that extends the reach of that signal to the edge.
Domain Expertise
Bringing the deepest operational know-how.
They’ve spent more than a century inside energy grids, rail networks, manufacturing lines, water systems, and more – and their HMAX portfolio and OT/IT integration work represent some of the deepest operational know-how in the industry. For Edgescale, Hitachi is both a go-to-market partner for industrial customers and a source of ground truth on what Physical AI actually has to survive in the field – the safety constraints, the legacy protocols, the regulatory reality. They translate the Edgescale Physical AI platform into solutions their customers already trust them to deliver.
INTEGRATIONS & CONNECTIONS
Bringing all your data together.
The Cube connects, aggregates, and organizes information from any source — without complex pipelines or data engineering — and makes it readily usable by your applications.
