Turn an AI workload into an infrastructure plan your IT and project teams can deliver and operate. Express Projects connects capacity and software requirements with site readiness, deployment, validation and ongoing management. Branded compute platforms and components can be supplied as part of the project; custom configurations are assessed where the requirement calls for them.
What to prepare
- AI workload, software stack, indicative demand and growth
- Data location, hosting preferences and existing infrastructure
- Site capacity, validation criteria and operating responsibilities
What you receive
- Workload requirements and infrastructure design decisions
- Site-readiness, deployment and validation plan
- Configuration evidence and continuing operating handover
Explore the project structure
Start with training or inference needs, then size the accelerator and host resources together. Storage throughput, network interfaces, rack power, cooling arrangements and software compatibility belong in the same design.
Conceptual planning view. Final architecture is agreed for the project.Define the workload and acceptance criteria
Inference, development and training place different demands on GPU memory, host resources and data access. Capture model requirements, concurrency, data volumes, software dependencies and expected growth. Agree a representative workload and test conditions so platform choices can be assessed against the intended use.
Design the environment and prepare the site
Plan compute, storage, networking, identity and management access together. Compare on-premises and cloud placement against data location, connectivity, cost and operating ownership. Confirm rack dimensions, power allocation and cooling arrangements with the facility and platform providers; specialist facility services are separately scoped.
Deploy and validate the agreed platform
Coordinate installation, storage and network access, approved drivers and the agreed software environment. Check user permissions and infrastructure health before running the validation workload. Record software versions, test conditions, results and unresolved actions for technical acceptance.
Operate and expand with clear responsibilities
Define monitoring, capacity reviews, patch and driver changes, backup responsibilities and escalation routes. Hardware support, infrastructure operations and model or application work have distinct owners. Review compatibility and site capacity before expansion; performance objectives and service coverage follow the agreed design and contract.
Include equipment supply where needed
Assess suitable branded server, accelerator, storage and network options against the design, compatibility and support requirements. Availability, configuration and warranty arrangements are confirmed in the proposal. Custom assembly and OEM / ODM enquiries are additional routes where standard configurations do not fit, with their own validation and support scope.
Technology for this environment
Explore the platforms behind the specification, installation and operating plan.
Custom configuration examples Optional
AI compute, configured around the workload.
Choose a starting point, then build the specification around the applications, site and operating plan.
Express AI G6
A larger rack platform for a workload-led GPU build. Accelerator choice, host resources, storage and power are assessed as one system.
Reference platform: TA-S8621A4Discuss this configuration
Express AI G4
A 4U chassis option to assess for a custom compute or accelerator build. The platform and component list are selected and checked for each enquiry.
Reference platform: TA-S5888G1Discuss this configurationConfiguration examples. The proposal confirms the component list, compatibility, warranty arrangements and delivery scope.