AI & HPC infrastructure consulting

We start with the applications, datasets, model sizes and users that will share the system. Interactive notebooks, overnight simulations and public inference endpoints place different demands on infrastructure. The discovery brief records existing bottlenecks, required completion times, sensitive data boundaries and growth assumptions so the proposed architecture has an identifiable purpose.

Compute, memory, accelerator capacity, storage and networking are considered together. A large GPU allocation is not useful if the dataset cannot reach it or the application cannot use it. We compare a workstation, a shared server and a cluster against your concurrency and expansion needs, separating essential capacity from optional future additions.

The assessment includes rack space, electrical supply, cooling, connectivity, access control and the team responsible for day-to-day operation. Facilities work and IT deployment are listed separately. Existing equipment may be reused where its condition, compatibility and support position are acceptable; those decisions are recorded rather than assumed.

The output can include an architecture diagram, itemised bill of materials, software requirements, implementation stages and a proposed acceptance exercise. Procurement teams can compare equivalent scope, while technical teams can review how the configuration will be tested. Benchmark figures are included only when their method and operating conditions are available.

Consulting fees depend on the number of workloads, sites, stakeholder sessions and the depth of benchmarking required. The proposal separates advisory work, any paid hardware access, travel and subsequent implementation. Share a requirements note or existing bill of quantities to receive a scoped quotation; equipment purchasing remains a separate decision.