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AI server builds
Tell us the model, application and scale. We’ll check the GPU, server, memory, storage, networking and software before quoting.
Start with your workload
Start with the application, scale and where it will live. We’ll use that to narrow the server, GPU, memory, storage and networking.
See what shapes the buildReal-time or batch inference shaped by latency, throughput, concurrency and deployment density.
Size model training and fine-tuning around GPU memory, scale, data movement and software.
Language models, RAG, embeddings and agent systems shaped around the intended operating model.
Image and video analytics across ingest, resolution, model complexity and response targets.
Engineering and scientific workloads driven by precision, bandwidth, scale and data movement needs.
Professional graphics and virtual desktops with user, software and deployment-density context.
Leave anything you do not know blank. We’ll ask for it if we need it.
Example AI server builds
Workstation · desktop / tower
Desk-side professional GPU system for development, fine-tuning, visualisation and local AI.
Examples only. Final parts, price and availability depend on your completed brief.
Use this starting point
Rack-efficient · inference
A compact, low-latency inference system for edge, branch, lab or rack deployments.
Examples only. Final parts, price and availability depend on your completed brief.
Use this starting point
Balanced · training / inference
A balanced server for inference, fine-tuning, rendering and analytics that need more headroom.
Examples only. Final parts, price and availability depend on your completed brief.
Use this starting point
High-density · training / HPC
A dense platform for demanding training, HPC and large-model inference.
Examples only. Final parts, price and availability depend on your completed brief.
Use this starting point
Scale-out · cluster / production
Multiple servers for distributed training, shared inference and future growth.
Examples only. Final parts, price and availability depend on your completed brief.
Use this starting point
Check the whole system
The GPU is only one part of the build. We also check the server, data path, environment, software, budget and timescale.
Choose a server platform
Enterprise rack and accelerator platforms with HPE management and serviceability in mind.
Dense compute and modular PowerEdge servers for accelerated enterprise workloads.
Flexible ThinkSystem servers for accelerated compute and scale-out deployments.
Add the memory, storage, networking and software to the same server brief.
We never assume a GPU fits a server. We check the chassis, riser, power, airflow, cooling, firmware, warranty, availability and licensing before quoting.
Your build details
Start with the outcome, preferred build type or an existing bill of materials. Leave any unknown details blank.
Your build brief
This is a brief, not a final buildFit, price, availability and licensing are confirmed on the quote.
Frequently asked questions
Start with the application, model, scale, concurrency and where the system will run. The example builds help you prepare the brief; the final parts are set on the quote.
Yes. We can put the server, GPU, CPU, DDR5 ECC memory, NVMe storage, networking, software, licensing and warranty on one quote.
Yes. Add the known manufacturers, models, SKUs and technical details to the build brief. We’ll check the complete platform before pricing it.
Yes. A GPU preference is optional. Share the intended outcome, model or application, scale and deployment location. Leave anything you do not know blank.
Yes. We can include the software and licences. We check the edition, entitlement, support and compatibility against the intended environment before quoting.
Yes. Include the scale, data movement, networking, power, cooling and deployment constraints. We’ll check the complete build before quoting.
The quote states the final platform, availability, price and licences.