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High-density AI data centre server hall with GPU compute racks and structured cabling
AI Infrastructure

Infrastructure engineered for AI workloads.

AI computing requires more than high-performance accelerators. It requires a coordinated infrastructure architecture capable of supporting demanding power, cooling, networking and storage requirements.

Discuss AI InfrastructureAll capabilities
The AI infrastructure stack

A complete architecture for accelerated computing.

  1. 01

    Accelerator hardware

    GPUs, CPUs, memory and interconnects selected for the intended training or inference workload.

  2. 02

    Rack architecture

    Power density, physical layout and thermal interfaces engineered around the accelerator platform.

  3. 03

    Networking

    Scale-up and scale-out fabrics sized for cluster communication without becoming the bottleneck.

  4. 04

    Storage

    Datasets, checkpoints and model-serving requirements planned as part of the compute architecture.

  5. 05

    Facility infrastructure

    Electrical power, cooling and resilience that keep accelerated halls available under sustained load.

Layered isometric illustration of an AI data centre architecture stack
Close-up of a high-density AI GPU server rack with fibre and cooling interfaces
GPU infrastructure

Built around the requirements of accelerated computing.

We evaluate GPU server configurations, rack density, memory architecture, interconnects and infrastructure requirements against the intended workloads.

Technology assessment may include NVIDIA HGX, DGX, Blackwell and Vera Rubin platforms, as well as comparable accelerator technologies.

Training and inference

Different workloads. Different infrastructure demands.

  • AI Training

    Large-scale accelerator clusters require high-bandwidth communication, storage throughput, power availability and sustained thermal performance.

  • AI Inference

    Production inference environments require predictable latency, concurrent request capacity, efficient resource utilisation and workload-specific energy performance.

Technology ecosystem

The platforms we engineer around.

We show technology categories — not unsupported partnership badges — so the conversation stays grounded in the architecture your facility needs.

  • GPU and accelerator platforms
  • High-speed Ethernet
  • InfiniBand networking
  • Enterprise storage
  • Liquid cooling systems
  • Workload orchestration
High-performance AI data centre networking with organised optical fibre cabling
Next steps

Planning an AI computing facility?

Let's discuss your accelerator platform, capacity and infrastructure requirements.

Talk to an AI Infrastructure Consultant