AI Datacenter

AI Datacenter Design & Build

From architecture to 24/7 operations — entrust your AI infrastructure to the AI Datacenter Engineers team.

We don’t just deliver hardware — we build a complete ecosystem

Our specialized engineering team provides a full service

Design

Build

Operate

We design high-performance cooling and power solutions, deploy NVIDIA DGX/HPC clusters, and ensure continuous monitoring and operation.

WHAT DOES A FULL-CYCLE AI DATA CENTER DELIVERY INCLUDE?

End-to-end architecture and design

Our engineers design energy-efficient data centers optimized for HPC and AI workloads, combining advanced cooling, security solutions, and scalability.

Data center construction and integration

We don’t just design — we deliver full implementation: power and cooling infrastructure, site preparation, and deployment of network and server architecture.

NVIDIA DGX and HPC cluster deployment

Our team specializes in deploying NVIDIA DGX systems, GPU servers, and AI/HPC clusters, optimizing performance, ensuring compatibility with existing infrastructure, and providing unified management for easier administration.

24/7 monitoring and operations

AI environments require continuous monitoring, performance analytics, and fast incident response. We provide full operational management to keep your data center stable, secure, and efficient.

WHY DO COMPANIES CHOOSE

DATAKOM + AI DATACENTER ENGINEERS

AI and HPC engineering team

A specialized AI and HPC engineering team with international experience.

Full-cycle delivery in one place

from concept and architecture to construction, cluster configuration, and ongoing operations.

Vendor-independent approach

we select solutions that best match your performance and budget requirements.

Faster time to AI value

a precisely designed and optimized data center enables quicker AI model deployment and accelerates research and business processes.

WHO IS THIS SOLUTION FOR?

Get a full AI infrastructure ecosystem, not just hardware.

We deliver a complete Design–Build–Operate lifecycle — from architecture and cooling solutions to NVIDIA DGX cluster deployment and 24/7 monitoring.

Organizations planning to build an AI or HPC computing center

Companies looking to scale GPU capacity or migrate to the NVIDIA DGX platform

Institutions that require high data security and on-premises infrastructure

Startups and research centers that need a flexible and reliable AI environment

FREQUENTLY ASKED QUESTIONS (FAQ)

What is an AI data center, and how is it different from a traditional data center?

An AI data center is a purpose-built infrastructure designed to run GPUs, NVIDIA DGX systems, high-performance computing (HPC) servers, and compute-intensive workloads.

Key differences include:

Higher power and cooling requirements
Higher equipment density
Specialized network architecture (e.g., InfiniBand)
Optimized room layout and airflow design

Traditional data centers are often not designed to support modern AI workloads efficiently.

What company requirements should be defined before designing an AI data center?

We begin with an analysis of performance, data volume, security, and scalability requirements. Key questions include:

How many GPUs and what type of clusters are required?
Is NVIDIA DGX or another HPC platform planned?
What power and cooling capacity is available?
What is the expected infrastructure growth over the next 12–36 months?

This ensures an energy-efficient architecture that can scale with future workloads.

How long does a Design–Build–Operate AI data center project take?

Depending on project size and complexity, typical timelines are:

4–6 weeks – architecture and technical design
2–5 months – site preparation, power, and cooling infrastructure
1–3 weeks – NVIDIA DGX/HPC integration and configuration

The full cycle usually takes 3–8 months.

Is it possible to upgrade an existing data center for AI workloads?

Yes. Many clients choose to modernize their current infrastructure by:

Expanding power and cooling capacity
Upgrading network and server architecture
Integrating GPU clusters
Adapting facilities for higher-density equipment

This allows a transition to AI computing without a complete rebuild.

Can an AI data center be deployed in a small organization?

Yes — thanks to a modular approach.

We provide solutions for:

Small installations (desktop-sized systems or single 2U racks)
Mid-sized organizations (10U and larger systems, including distributed clusters)
Large national-scale HPC centers

AI infrastructure is tailored to your business size, budget, and performance needs.

What cooling solutions are suitable for AI and NVIDIA DGX systems?

Cooling options depend on power density:

Air cooling – suitable for smaller GPU clusters
Liquid cooling – ideal for intensive AI workloads and DGX systems
Direct-to-chip and rear-door cooling – energy-efficient and quiet

We select the cooling model that delivers maximum performance with optimal cost efficiency.

Do you provide 24/7 monitoring and operations management?

Yes. Our full-cycle service includes:

Continuous infrastructure monitoring
Alerting and incident management
Performance analytics and optimization
Regular reporting and recommendations
Proactive security monitoring

This ensures your AI data center operates securely and efficiently at all times.

How much does it cost to build an AI data center?

Costs depend on several factors:

Selected GPU/DGX infrastructure
Power and cooling requirements
Readiness of the data center facility
Security and network architecture

Typical investments range from €50,000 for small installations to several million euros for large HPC centers.

We always provide a detailed cost estimate after the initial requirements analysis.

Can AI Datacenter Engineers deliver international projects?

Yes. The team works across the Baltics, the EU, and globally, with a strong focus on AI and HPC infrastructure projects. This is especially important for organizations building regional or international AI computing centers.