SOLUTIONS / PRIVATE AI INFRASTRUCTURE
AI infrastructure.
Planned as a system.
Scope the complete environment for inference: compute, enclosure, power, cooling and connectivity. Each workstream starts with your requirements and ends with defined interfaces and responsibilities.
01 / Modular AI shelters
A dedicated place for your compute.
Telecom-style shelters and walk-in enclosures configured around equipment access, environmental conditions and future expansion.
Decisions to resolve
Rack count and density; equipment replacement routes; enclosure dimensions; cooling arrangement; power distribution and monitoring.
Define in the project scope
A concept layout, site interfaces, equipment requirements and installation dependencies.
Design principle: size the shelter around the equipment and its maintenance needs.
02 / Power & thermal planning
Make the site ready for the load.
Assess utility capacity, backup power and heat rejection together with site access, permitting and operating conditions.
Decisions to resolve
Available electrical capacity; expected IT load; backup duration; cooling method; ambient conditions and service access.
Define in the project scope
A load basis, capacity constraints, resilience options and the utility or specialist inputs still required.
Design principle: evaluate grid, off-grid or hybrid options against the location and operating requirements.
03 / Fibre & network integration
Connect compute to the operation.
Plan the path between your users, datasets, AI servers and external services.
Decisions to resolve
Carrier access; bandwidth; storage traffic; switching; network separation; redundancy and monitoring.
Define in the project scope
A connectivity concept, carrier dependencies and performance criteria for validation.
Design principle: assess application latency and availability across the complete path.
Enterprise platforms for AI inference
Choose infrastructure around the workload, with server options from established manufacturers.
- Supermicro SYS-521GE-TNRT — a 5U GPU platform with supported NVIDIA L4 and L40S configurations.
- Dell PowerEdge R760xa — a GPU-optimised, air-cooled 2U server for workloads including inference.
- HPE ProLiant DL380a Gen11 — a 2U accelerator platform with supported L4 and L40S options.
- Lenovo ThinkSystem SR650 V3 — a 2U enterprise server with documented L4 and L40S support.
These are reference platforms for discussion. Final selection depends on model memory, concurrency, latency targets, validated configurations, availability and support requirements.
Start with a practical deployment plan
Share your use case, site location, target timeline and budget range. We will discuss the compute and infrastructure scope that fits your project.
Concept configurations shown. Final layouts, equipment and commercial scope are confirmed in each proposal.