Up to eight GPUs, outside the rack
Rack-class compute without a server room
Liquid-cooled workstations with the same eight-GPU compute as our rack server, built around the workloads you plan to run and upgradeable as they grow.
On the workstations page
How many GPUs, and which chassis? An engineer sizes it with you.
LM TEK 4U8GPU10KW
8-GPU liquid-cooled AI server in a 4U envelope. Built around off-the-shelf internals and an EK-engineered cooling loop – designed for your server room, not a hyperscale facility.
Platform details
Plan and buy
Roadmap
Additional server platforms are added as released. Looking for something specific? Talk to engineering.
Where to begin
Two-minute assessment
Five questions on your workload and situation, routed to a personal next step.
Size a setup
AI Compute Configurator
Describe what you want to run and get an example build to plan around. A planning resource, not a quote.
Understand
What Generative AI Actually Is
A vendor-agnostic primer.
AI Workload Patterns
The five shapes deployments take.
Glossary
Deployment terms in plain English.
Plan your deployment
Deploying AI in Your Business
The journey – six phases.
Data Readiness for AI
The layer most deployments fail on.
From PoC to Production
The validation gate most projects stall at.
AI Infrastructure Buying Guide
Five staged investments, sized right.
Private AI for Sensitive Data
On-prem, air-gapped, regulated.
Why Sovereign Enterprise AI
Sovereign Enterprise AI
The case for control – why now.
The Engineering Case
The middle tier – why hardware-first.
Engagements scope the workload first, then the hardware. We engineer Layer 1 and orchestrate partners for Layers 2-3.
Operations · , Opinion
The steps that decide whether a first AI server pays off happen before the purchase order, not after delivery.
Glen Rhodes · 9 Oct 2026 · 4-min read
New articles and whitepapers, when they are published. No marketing.
LM TEK d.o.o. · Pod Lipami 10 · 1218 Komenda · Slovenia
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