Why this matters now
Pilots run fine on a single GPU. Production needs networking, storage, security, sovereignty, and operations that hold up at scale and under audit.
Production AI Stack
The GPU gets the attention, but the network fabric, storage layer, security controls and operating model decide whether the workload actually performs.
GPU platforms for training, inference, bare metal, virtualised or containerised workloads.
RoCE, InfiniBand, 1.6T capability and low-latency fabric design.
Parallel filesystems and AI-ready storage designed for throughput and latency.
Model registry, weight protection, prompt-injection defence and data loss prevention.
Cluster operations, scheduling, observability, capacity and cost optimisation.
What We Deliver
From design through procurement to managed operations. For neoclouds, AI builders, regulated enterprises and the public sector.
How We Work
Start from the model and the throughput targets. Work backwards to the right GPU, network, storage and software stack. Avoid generic templates.
We work across NVIDIA, AMD, Supermicro, Dell, HPE, Lenovo and the AI-native stack. Vendor-agnostic procurement, transparent margins.
Networking, identity, model security, residency, audit. Production-grade from day one, not retrofitted later.
Managed cluster operations, capacity planning, cost optimisation, model lifecycle, observability. Your team focuses on the AI, not the infrastructure.
Why CloudCoCo
NVIDIA and AMD GPUs, multiple storage and networking partners, multiple deployment options. The right architecture, not the most-incentivised one.
Most pilot infrastructure can't carry production. We design for governance, security, sovereignty and operations from day one.
UK-based engineers and operations team. Useful when sovereignty matters and when something goes wrong at 3am.
Transparent pricing, no opaque rebates, no vendor-driven design. We work for the customer, not the manufacturer.