AI infrastructure
Build your AI‑ready infrastructure
Every layer an AI system runs on: GPU workstations and servers, plus the memory, storage, networking, power and racks around them. One supplier, from a single desk to a full data center.
How it fits together
Seven layers under every AI system
An AI system is only as fast as its weakest layer. GPUs need fast memory and storage to stay busy, a network that can move data between machines, and power and cooling that can handle dense, hot hardware.
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Your AI workloads
Model training, fine-tuning, inference and retrieval (RAG) run on top, on hardware you own and control.
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Management & security
KVM consoles, remote management (BMC/IPMI), TPM modules and door access keep the stack reachable and protected.
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Compute & GPUs
GPU servers, workstations, server motherboards and accelerators do the actual training and inference.
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Memory & storage
ECC DDR5 memory, NVMe drives and NAS keep datasets close to the GPUs, so expensive compute is not left waiting.
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Network fabric
Switches, routers and network adapters move training data and model traffic between servers, storage and users.
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Racks & cabling
Cabinets, rails, patch panels and cable management keep hardware serviceable and airflow clean.
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Power & cooling
Dense GPU hardware draws a lot of power and turns it into heat. Online UPS systems, metered PDUs and server-grade coolers keep it running.
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From desk to data center
How AI infrastructure grows
Most teams start small and scale up. The same layers appear at every stage; what changes is how many of each you need and how much power, cooling and network capacity sits around them.
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Stage 1
AI workstation
For developers, researchers and small teams building and testing models.
Typical setup: One or two professional GPUs, a workstation CPU and board, plenty of ECC memory, fast NVMe storage and a high-wattage power supply.
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Stage 2
Server room
For a business running private AI or inference on its own premises.
Typical setup: One rack with GPU and CPU servers, a top-of-rack switch, storage, a rack UPS, PDUs and a KVM console.
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Stage 3
Enterprise row
For several teams sharing GPU capacity across projects.
Typical setup: A row of racks with redundant switching, shared storage, in-row cooling, overhead cable trays and metered power.
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Stage 4
Data center
For hosting providers, research groups and large-scale training.
Typical setup: Rows of racks in hot and cold aisles, dedicated power rooms, cooling units and a high-bandwidth network fabric.
More GPUs, more power, more cooling, more bandwidth
Inside the rack
What goes into an AI rack
A typical 42U rack for AI, from the patch panel at the top to the UPS at the bottom. Heavy equipment goes low, networking goes high.
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Patch panel
Terminates structured cabling so servers can be re-patched without re-running cable.
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Top-of-rack switches
Connect every server in the rack and uplink to the rest of the network.
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KVM console
One screen and keyboard in the rack for setup and emergencies.
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GPU servers
4U servers with room for several full-height GPUs and the airflow to cool them.
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CPU and inference nodes
Compact 1U servers for inference, data preparation and serving APIs.
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Storage
NVMe and SAS storage for datasets, checkpoints and model files.
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Rack PDUs
Distribute power to every device and show how much each rack draws.
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UPS and battery
Ride through outages and shut servers down cleanly.
CyberPower OLS6000ERTXL3U online UPS CyberPower BPSE48V40ART2U battery pack
The empty space in the middle is deliberate. Leave room to add GPU servers as demand grows, and check that power and cooling can take the extra load before you fill it.
Shop by layer
Products for every layer
A selection from our catalog. Each product page shows current pricing, availability and full specifications.
Compute & workstations
Servers, workstations and server motherboards
- Supermicro SuperWorkstation SYS-531R-ITower workstation platform
- Supermicro SYS-E403-14B-FRN2TCompact edge server
- Gigabyte R133-C11-AAG11U rack server
- Supermicro MBD-H13SRA-TF-BServer motherboard, AMD EPYC (SP5)
- Gigabyte MZ33-AR1Server motherboard, AMD EPYC (SP5)
- ASRock Rack SIENAD8UD3Server motherboard, AMD EPYC (SP6)
- ASRock WRX80 Creator R2.0Workstation motherboard, Threadripper PRO
GPUs & accelerators
Training, inference and visualization
- AMD Instinct MI100Data center accelerator, 32 GB HBM2
- PNY NVIDIA RTX 2000E Ada Generation16 GB, low-profile professional GPU
- ASUS ProArt GeForce RTX 4080 SUPER OC16 GB, for AI development workstations
- Gigabyte GeForce RTX 4080 SUPER Gaming OC16 GB
Memory & storage
Keep data close to the GPUs
- Kingston FURY Renegade Pro 128 GB DDR5 kit4 x 32 GB, DDR5-5600, ECC registered
- Samsung 16 GB DDR5 RDIMMDDR5-5600, ECC registered
- Supermicro NVMe backplaneNVMe drive backplane
- InLine MCIO x4 cable, 0.5 mFor PCIe and NVMe connections
- QNAP TBS-H574TX5-bay all-flash NAS
- Seagate IronWolf 4 TBNAS hard drive
- HPE 900 GB SAS drive2.5-inch enterprise hard drive
Networking
Switching, routing and connectivity
- Cisco Catalyst C9300L stack kitStacking kit for Catalyst 9300L
- Cisco PWR-C1-350WAC-P=350 W AC power supply for Catalyst 9300
- Cisco ISR4221/K9Integrated services router
- TP-Link Omada SG3210X-M22.5 GbE managed switch with 10G SFP+
- MikroTik RB5009UG+S+INRouter with SFP+ port
- Lenovo ThinkSystem network adapterServer network adapter
Power, cooling & racks
Keep dense hardware powered and cool
- CyberPower OLS6000ERTXL3UOnline UPS, rack or tower
- CyberPower BPSE48V40ART2U + RMCARD400Extended battery pack and network card
- Eaton ePDU G3 EILB13Inline monitored PDU
- CyberPower PDU81005Rack PDU
- APC Easy Rack ER640224U network cabinet
- Supermicro MCP-290-00058-0NRack rail kit
- Noctua NH-U14S TR5-SP6CPU cooler for SP6 and TR5 sockets
- Seasonic PRIME PX-16001600 W workstation power supply
Management & security
Reach, control and protect the stack
- ATEN CL6700MWLCD KVM console drawer
- ATEN CS1734B4-port KVM switch
- ATEN CV211Laptop USB console adapter
- ASUS ASMB10-iKVMRemote management (BMC) module
- Supermicro AOM-TPM-9670V-STPM 2.0 security module
- Gigabyte CTM010TPM 2.0 security module
- Ubiquiti UniFi Access G3 IntercomDoor access for server rooms
Before you order
AI infrastructure planning checklist
Seven things to check before the hardware arrives, whatever the size of the build.
Power per rack
Add up the maximum draw of every device. A single multi-GPU server can draw several kilowatts, so check circuits, PDUs and UPS ratings before the hardware arrives.
Cooling and airflow
Heat output follows power draw. Plan airflow direction, blanking panels and hot and cold aisles so GPUs do not throttle.
Network bandwidth
Match switch uplinks and network adapters to how much data moves between storage and GPUs. 1 GbE is rarely enough for training data.
Storage speed and size
Use fast NVMe for active datasets and checkpoints, and larger drives or NAS for archives and backups.
Memory
Server and workstation boards use ECC registered DDR5 (RDIMM). Match the speed your board supports and fill memory channels evenly.
US power and plugs
Many server components are sold for several markets. Check input voltage, plug type and certifications on each product page before you order.
Remote management
BMC/IPMI, KVM access and TPM modules let you manage and secure servers without walking to the rack.
Why NetworkDistri
One partner for the full build
One supplier for the whole stack
Compute, GPUs, storage, networking, power and racks from one order and one invoice.
Quotes for projects and volume
Send us your bill of materials or requirements and we will quote the full build.
Business accounts
Order as a business with quotes, proforma invoices and trade accounts.
Questions about AI infrastructure
What hardware do I need to run AI models on-premises?
At minimum you need a GPU-equipped workstation or server with enough memory and fast NVMe storage. As you grow, you add networking between servers, shared storage, rack power and UPS protection, cooling, and remote management.
Should I start with a workstation or a server?
A workstation suits one person or a small team building and testing models at a desk. A rack server suits shared use, around-the-clock inference and growth, because it fits in a rack with shared power, cooling and networking.
How much power does an AI rack need?
It depends on the servers in it. Add up the maximum draw of every device and leave headroom. A single multi-GPU server can draw several kilowatts, so dense GPU racks often need higher-capacity circuits, PDUs and UPS systems than a typical office rack.
Can you supply a complete server room or data center project?
Yes. We supply hardware across the whole stack and quote for projects and volume orders. Send your requirements or bill of materials through the quote form and our team will reply.
Are these products suitable for US power?
Many are, but some products are sold for several markets. Check the input voltage, plug type and certifications on each product page, or ask our team to confirm before you order.
Are prices and stock shown on this page?
No. This page shows examples from our catalog. Each product page shows the current price and availability.
Plan your AI build with us
Send us your requirements or a bill of materials, from one GPU workstation to a full rack or more, and we will quote the complete build.
Products shown are examples from our catalog. Specifications, availability and pricing are on each product page and can change. Check input voltage and plug type for US installations. Product names and trademarks belong to their owners.
