[ Service ]

Edge AI Data Centers

Modular AI compute placed close to the data and the people who use it.

[ Overview ]

Not every AI workload belongs in a distant hyperscale region. Modular, edge-sited compute can bring inference and training closer to where data is produced, with lower latency and more control over residency. We assess sites, size the capacity and plan the power and cooling behind it.

[ What we do ]

Site selection and feasibilityLand, power, fibre, zoning and permitting.
Capacity planningGPU and compute sizing against your workloads.
Modular designContainerised compute that scales in steps.
Power and coolingOn-site generation, storage and efficient cooling designed in.
ConnectivityFibre paths and network design for edge sites.

[ Built in steps ]

Start with one module. Add the next when demand arrives.

The first module goes live on the power already available; the next ones are planned on the same site from day one.Scroll sideways ›

[ Inside the module ]

Racks and cooling, designed together.

Rows of high-density racks on one cooling loop — sized for the workload, not for a generic floor.Scroll sideways ›

[ Power for the site ]

Every source the site needs, feeding one compute block.

Grid, storage, solar, fuel cells and backup generation, combined to match the site and the load.Scroll sideways ›

[ What changes ]

01
Compute where it is needed
02
Control over data residency
03
Capacity that grows with demand

[ More in Digital Infrastructure ]

Campus Data Centers ›Battery System Solutions ›Renewable Energy ›

[ Contact us ]

Bring us the business problem.

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