Independent, hands-on guidance for organizations planning or scaling AI infrastructure — for commercial products and research programmes alike. We advise on the same class of systems we design, integrate and run in production.
01
Architecture & sizing
GPU cluster, storage and network design matched to your workloads — capacity planning, benchmark-driven sizing and a scaling path that doesn’t paint you into a corner.
02
Build, buy or cloud
Vendor-neutral comparisons of on-premises, colocation and cloud options — total cost of ownership, procurement support and hardware selection you can defend to a board or a funding body.
03
Facility readiness
Power, cooling, space and availability targets checked against what dense AI hardware actually demands — with Uptime Institute–accredited designers when the facility itself needs work.
04
Platform & operations
Orchestration, model-serving stacks, monitoring and observability — the software layer that turns racks of GPUs into a platform teams can actually use.
Who it’s for
Companies building AI products or bringing inference in-house, and research organizations — universities, institutes and grant-funded projects — that need infrastructure decisions to hold up for years, not just for the next milestone. Engagements range from a focused review of an existing plan to full support from requirements through procurement and commissioning.