Compute starts with the system.
Plan GPU facilities with direct-to-chip cooling and high-bandwidth networking for training and inference.
Explore approach ↗InfrastructureThe building is part
The building is part
of the compute system.
We design compute, cooling, power, and network fabric as connected parts of an AI environment. Hardware, deployment regions, and capacity are scoped for each engagement.
An environment shaped around you.
Define dedicated capacity, private connectivity, and operating controls for your organization.
Explore approach ↗Coordinate the physical layer.
Bring power, cooling, network health, maintenance, and capacity planning into one operating scope.
Explore approach ↗Engineering design targetsDesign for the workload.
Design for the workload.
Validate at the site.
These planning figures come from our infrastructure design envelope. They describe targets, rather than measured operating results or available capacity.
| Rack power density | 100 kW+ design capability |
|---|---|
| Cooling loop | 30–35°C direct-to-chip design |
| Heat rejection | 120 kW CDU design |
| Energy efficiency | 1.12 annualized PUE target |
Final specifications depend on the site, selected hardware, environmental conditions, and operating requirements.
Start with your workloadWhat will you build
Talk to our teamWhat will you build
with better compute?
Bring your model, scale, and deployment goals. Let’s map the software and infrastructure to the work.