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Dedicated Bare-Metal Compute
Dedicated GPU infrastructure for AI training, inference, scientific computing and other high-performance workloads requiring predictable resources and direct hardware access.
Global AI compute infrastructure
AI moves fast. Infrastructure must move faster.
AI GPU Data Center is developing dedicated, high-density GPU infrastructure for organisations that require bare-metal performance, reserved capacity and greater control over critical compute.
Planned initial architecture: NVIDIA B300 · 1MW first phase · Expansion aligned with demand
- Power — grid supply enters the unit
- Cooling — thermal capacity above the racks
- Network — interconnect and transit below the racks
- Unit 01 — 1MW planned first-phase capacity
- Expansion — phased pathway towards 5MW
Development plan
All figures below describe planned infrastructure. Nothing shown here is operational today.
B300
Planned initial GPU architecture
1MW
Planned first-phase capacity
5MW
Planned phased expansion pathway
Bare Metal
Dedicated client infrastructure
Offtake
Capacity aligned with contracted demand
Unit 01
The first module is ordered and underway.
Equipment for the first modular deployment — the unit itself, racks, chillers and cooling — has been ordered, together with eight Supermicro NVIDIA HGX B300 servers carrying 64 B300 GPUs.
- Status
- Equipment ordered — modular unit, racks, chillers and cooling
- Initial compute
- 8 × Supermicro NVIDIA HGX B300 servers — 64 B300 GPUs
- Pre-provisioned capacity
- 16 servers / 128 GPUs within the same module
- Cooling
- Rear-door heat exchangers matched to high-density racks
- Module cadence
- Further modules planned on an approximately quarterly import cycle
Latest development updates
Progress, dated.
First B300 modular data centre deployment underway
Orders have been placed for the first modular data centre unit, including racks, chillers and cooling, together with eight Supermicro NVIDIA HGX B300 servers carrying 64 B300 GPUs.
The capacity constraint
Compute is no longer a utility. It is strategic infrastructure.
AI workloads are expanding faster than conventional infrastructure can be planned, financed and deployed. Access to the right hardware is only one part of the constraint. Power, cooling, networking, storage, operations and long-term capacity must function as one integrated system.
AI GPU Data Center is being developed around that full infrastructure requirement.
- 01
Power
Supply, distribution, redundancy
- 02
Facility
Cooling, density, physical security
- 03
Compute
GPU, CPU, memory
- 04
Network
Interconnect, storage, transit
- 05
Workload
Training, inference, research
One integrated system — a constraint in any layer becomes a constraint on the workload
What we provide
Infrastructure designed around the workload.
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Client-Specified Architecture
GPU, networking, storage and operational configurations designed around the client's workload, scale, security and deployment requirements.
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Managed GPU Infrastructure
Dedicated capacity supported through monitoring, infrastructure operations and lifecycle planning under an agreed service framework.
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Capacity Reservation and Offtake
Structured reservations and client offtake agreements align infrastructure expansion with contracted demand and provide a defined pathway to future compute capacity.
From hardware to capacity
More than GPUs. A complete compute environment.
AI GPU Data Center's infrastructure model treats compute as an integrated physical and operational system. Hardware selection remains configurable according to workload requirements, with NVIDIA B300 systems forming the planned initial build-out.
Layer 01
GPU systems
High-density accelerated compute forming the core of each deployment. NVIDIA B300 systems are the planned initial architecture; alternative configurations remain available according to client requirements.
Phased development
Capacity that grows against real demand.
Phase 01
1MW planned initial deployment
Dedicated high-density infrastructure based on NVIDIA B300 systems, subject to final engineering and client requirements.
Expansion
Phased pathway towards 5MW
Additional capacity developed according to client uptake, power availability, technical requirements and contracted offtake.
Future Scale
Repeatable infrastructure growth
A modular operating model designed to support additional capacity and future infrastructure locations as demand develops.
Client offtake
Secure capacity before the constraint reaches you.
For organisations with substantial future compute requirements, capacity cannot always be procured reactively. AI GPU Data Center works with prospective clients to define workload demand, infrastructure requirements and long-term capacity reservations.
Structured offtake agreements can provide the commercial foundation for phased infrastructure deployment while giving clients a clearer path to dedicated capacity.
- 01
Define workload
Establish workload profile, scale, data characteristics and growth expectations.
- 02
Design infrastructure
Configure GPU, interconnect, storage, power and operational requirements.
- 03
Structure capacity commitment
Agree reserved capacity, term and the commercial framework for offtake.
- 04
Deploy and operate
Phased deployment against the agreement, with managed infrastructure operations.
Built for consequential workloads
For organisations that cannot treat compute as an afterthought.
- Global enterprises
- Governments and public institutions
- AI and machine-learning companies
- Regulated and data-sensitive organisations
- Scientific and research institutions
- Organisations requiring dedicated bare-metal compute
- Infrastructure and capacity partners
Indicative organisation types only. No listed organisation is a current AI GPU Data Center client.
Why AI GPU Data Center
Dedicated compute. Engineered for demand.
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Dedicated by Design
Infrastructure planned around defined client workloads rather than generic shared-cloud availability.
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Demand-Aligned Growth
Capacity expansion anchored by commercial demand, reservations and client offtake.
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Hardware Flexibility
GPU and supporting infrastructure selected according to technical and commercial requirements.
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Managed Operations
Infrastructure operation remains part of the service rather than becoming an additional client burden.
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Strategic Capacity
Long-term access to compute treated as an infrastructure decision, not merely an hourly purchase.
Responsible infrastructure
Scale must be engineered responsibly.
AI GPU Data Center's development framework prioritises efficient infrastructure, demand-aligned expansion, responsible procurement and transparent governance. Environmental and operational commitments will mature alongside the physical infrastructure.
Framework pillars
- Energy and resource efficiency
- Demand-aligned expansion
- Responsible procurement
- Hardware lifecycle
- Skills and economic participation
- Governance and transparency
Plan the capacity your next phase requires.
Speak to AI GPU Data Center about dedicated GPU infrastructure, capacity reservations, client offtake or strategic infrastructure partnerships.
Content on this site describes planned infrastructure. See our infrastructure and capacity disclaimer.