AI Infrastructure Solutions

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Enterprise-grade AI computing as part of Virtualtek’s integrated stack — AI, Virtualization, and Enterprise Storage.

GPU Servers |AI Clusters | Edge AI | AI Storage

One Partner for Complete AI Infrastructure
Audit • Architecture • Integration • 360° Support


From initial assessment to ongoing operations – Virtualtek delivers complete AI infrastructure solutions with single-point accountability.

Book Your Complete Assessment

AI Workloads and Infrastructure Needs

AI infrastructure must adapt to the workload it supports. Each use case has unique demands in terms of compute, networking, and storage.

High-Performance Computing (HPC)

What it is
Simulation, modeling, and data-intensive science with tightly coupled parallel jobs.

Business segments
Engineering (CFD/FEA), energy, weather, life sciences, university HPC centers.

Infrastructure profile

  • Compute: Multi-node clusters; GPU acceleration where applicable.

  • Interconnect: InfiniBand for low-latency, high-throughput MPI-style workloads.

  • Storage: Parallel/scale-out file systems; NVMe tiers for scratch and checkpoints (Open-E, StorONE, Infortrend options).

  • Scheduling: Kubernetes-ready or traditional HPC schedulers alongside container workflows.

Visual Computing & Rendering

What it is
GPU-accelerated rendering, video processing, and VFX pipelines with high I/O demands.

Business segments
Media/VFX studios, broadcast, architecture & design, automotive visualization, gaming.

Infrastructure profile

  • Compute: GPU servers optimized for render and transcode; NVIDIA H100/A100/L40S or AMD MI300 as required.

  • Storage: High-throughput NVMe caches + scale-out storage for assets and frames.

  • Networking: NVLink intra-node; high-bandwidth fabric for shared asset pools.

  • Pipeline integration: Containerized workers orchestrated by Kubernetes for burst capacity.

Edge AI & IoT

What it is
Real-time inference close to data sources with environmental constraints and intermittent links.

Business segments
Manufacturing/quality, logistics, smart city, retail analytics, on-prem surveillance.

Infrastructure profile

  • Form factor: Compact, rugged systems for industrial reliability; −20 °C to +60 °C operation.

  • Connectivity: 5G/LTE, Wi-Fi 6; remote management for distributed fleets.

  • Compute: Efficient GPUs/accelerators sized for on-site inference.

  • Storage: Local NVMe for buffering; secure sync to central stores when links permit.

  • Orchestration: Lightweight container orchestration with central policy control.

Data Analytics & BI

What it is
Accelerated analytics combining batch, interactive queries, and real-time scoring.

Business segments
Retail, telecom, fintech, energy trading, customer intelligence platforms.

Infrastructure profile

  • Compute: GPU-accelerated nodes for SQL/ML acceleration where needed.

  • Storage: Tiered design — NVMe for hot data, scale-out/object storage for lakes and history (Open-E, StorONE, Infortrend supported).

  • Orchestration: Kubernetes-ready services for pipelines and micro-batch processing.

  • Integration: Works alongside virtualization stacks (VMware/XCP-ng) when required.

Machine Learning Operations (MLOps)

What it is
Deploying, monitoring, and updating models in production with automated scaling and CI/CD.

Business segments
Finserv/fraud, e-commerce personalization, ad tech, telecom, SaaS platforms.

Infrastructure profile

  • Compute: Balanced GPU/CPU nodes for online inference and batch jobs.

  • Orchestration: Kubernetes-ready clusters; containerized services; blue-green/rolling updates.

  • Networking: Low-latency east-west traffic; InfiniBand or high-speed Ethernet depending on SLOs.

  • Storage: Fast NVMe for feature stores and model artifacts; resilient object/scale-out tiers.

  • Compatibility: Works with VMware / XCP-ng when virtualization is required.

AI Training & Development

What it is
Large-scale deep learning model training with long runs, frequent checkpoints, and heavy parallelism.

Business segments
Research labs, AI startups, autonomous systems, medical imaging R&D, NLP/vision teams.

Infrastructure profile

  • Compute: GPU-dense servers, up to 16 GPUs per node; NVIDIA H100/A100/L40S or AMD Instinct MI300.

  • Interconnect: NVLink for intra-node bandwidth; InfiniBand for multi-node scaling.

  • Cooling/Power: Air or liquid options for sustained utilization.

  • Storage: High-speed NVMe for scratch; parallel/scale-out backends (e.g., Open-E, StorONE, Infortrend) for datasets and checkpoints.

  • Orchestration: Kubernetes-ready environments for job scheduling and resource isolation.

Why AI Infrastructure Demands a Structured Approach

Behind every AI project lies a maze of technical decisions. Rack size, power supply, cooling method, storage integration, virtualization layer — each choice influences the next, and each constraint must be addressed from the start. A facility’s available power or floor space can entirely redefine the architecture. Cooling alone may involve two radically different approaches: traditional air-cooling or advanced liquid-cooling.

At Virtualtek, we turn this complexity into a structured process. By aligning hardware, virtualization, and storage technologies from the very beginning, we make sure the final infrastructure is not only reliable and scalable, but also adapted to the real-world constraints of your data center.

Plan Your AI Infrastructure Today

Building AI infrastructure starts with choosing the right foundation. Get tailored recommendations based on your technical needs and project scope.

GPU Servers

The Foundation of AI Performance

Hundreds of GPU server configurations are available, each balancing compute power, scalability, and efficiency. The choice is immense — and selecting the right one depends on workload, power, cooling, and space constraints.

  1. CPU power without limits for every workload
  2. Scalable GPU acceleration—from 1 to 8 GPUs, NVIDIA or AMD
  3. Built for your environment: optimized for power, cooling, and space
  4. Enterprise-grade and certified for mission-critical uptime
  5. Future-ready architecture with next-gen expansion
GIGABYTE AI infrastructure GPU server platform - enterprise computing hardware for machine learning clusters and high-performance AI workloads

CPU Options


Support for Intel Xeon, AMD EPYC and Threadripper PRO families, optimized for AI and HPC workloads.

GPU Options


Latest NVIDIA and AMD accelerators, from 1 to 8 GPUs per system, certified for enterprise deployment.

Scalability & Form Factors


Flexible rack sizes, high-speed networking (10–400 GbE) and scalable storage for any data center.

Certifications & Reliability


Enterprise-grade systems, certified for mission-critical uptime with full OS/hypervisor compatibility.

Storage architecture depends on capacity requirements and use cases.

Analyze Your Storage Requirements

AI Clusters

GIGAPOD AI Clusters: Enterprise-Grade Supercomputing Infrastructure

What is GIGAPOD?

GIGAPOD is GIGABYTE’s factory-integrated AI supercomputing solution that eliminates the complexity of building GPU clusters from individual components.

Instead of months spent integrating servers, networking, cooling, and management software, GIGAPOD delivers a pre-validated, production-ready cluster that scales from 128 to 512+ GPUs with guaranteed performance and compatibility.

The Multi-Million Euro Integration Challenge

European enterprises attempting DIY AI clusters face 6-12 month integration timelines, compatibility issues between GPU servers and network fabric, cooling infrastructure redesign, and management software complexity.

A single misconfiguration can render hundreds of thousands of euros in hardware unusable for production AI workloads.

GIGAPOD Cluster Configurations:
  • Scalable clusters from 2 to 8 racks, supporting hundreds of NVIDIA or AMD GPUs.

  • Flexible air or liquid cooling options, compliant with European power standards.

  • Linear expansion possible without redesign or downtime.
Integrated Infrastructure:
  • High-speed interconnects (Ethernet/InfiniBand) with unified parallel storage for AI workloads.

 

  • Energy-efficient power and cooling design, fully CE and GDPR compliant.

 

  • Delivered and installed by certified engineers across Europe.
GIGABYTE POD Manager (Included): Complete Cluster Orchestration Platform
  • Centralized management console for clusters of any size, with automated workload scheduling and real-time performance analytics.

  • Enterprise integration via APIs and directory services, plus predictive maintenance for reliability.

Why European Enterprises Choose Virtualtek GIGAPOD:

  • Proven Reliability – Factory-tested clusters, zero compatibility risks
  • Faster Deployment – Production-ready in 3–4 months instead of 12+
  • Local Expertise – Certified engineers on-site across Europe
  • Predictable Costs & Compliance – Fixed pricing, EU data residency & safety standards

Edge AI

Real-Time AI Where Data is Created

Edge AI systems bring artificial intelligence processing directly to industrial sites, retail locations, and remote environments where data is generated. These ruggedized computing platforms deliver real-time inference without cloud connectivity dependencies, enabling millisecond response times critical for autonomous systems, predictive maintenance, and safety applications.

  1. Real-Time AI Processing – Inference without network latency
  2. Industrial-Grade Design – Reliable operation in harsh environments
  3. Seamless Integration – Ready for existing OT/IT systems with remote management
NVIDIA Jetson AGX Orin edge AI computing platform for industrial applications - 275 TOPS AI performance for real-time inference and autonomous systems

NVIDIA Jetson AGX Orin edge AI computing platform for industrial applications – 275 TOPS AI performance for real-time inference and autonomous systems

Compute Platforms


Latest NVIDIA and Intel edge platforms with dedicated AI accelerators.

Optimized for low-latency inference and scalable memory/storage options.

Environmental Specs


Built for rugged environments: wide temperature range, IP-rated protection, vibration resistance, and industrial connectivity (5G, LTE, Ethernet).

Deployment & Integration


Virtualtek handles site survey, connectivity planning, PLC/SCADA integration, and regulatory validation.

Remote monitoring ensures long-term reliability.

Applications & Use Cases


Predictive maintenance, smart city analytics, retail optimization, fleet monitoring, and energy grid management.

Why Choose Virtualtek for Edge AI Deployment

Deploying Edge AI in industrial environments requires more than standard IT skills.

Virtualtek combines certified Gigabyte hardware expertise with deep knowledge of OT/IT integration, delivering compliant and reliable edge systems across Europe.

Key differentiators:

  • Industrial Expertise – Beyond standard IT, tailored for harsh environments

  • OT/IT Integration – Specialists in PLC/SCADA and manufacturing systems

  • Local Support – Teams familiar with European industrial standards

  • End-to-End Delivery – From site survey to compliance and ongoing maintenance

Schedule Industrial Site Assessment

AI Storage

High-Performance Storage Architectures for AI Data Pipelines

What is AI-Optimized Storage?

AI workloads require sustained high-bandwidth storage, far beyond traditional enterprise systems. Optimized architectures deliver the low latency, scalability and throughput needed for training pipelines and large-scale datasets.

The AI Storage Performance Challenge

Standard NAS can’t keep up with GPU clusters that demand 100GB/s+ throughput. Without the right architecture, GPUs sit idle, training times explode and storage costs rise.

High-Performance Storage Tiers
  • NVMe flash arrays and parallel file systems deliver ultra-fast throughput.
  • Scalable designs grow linearly with your data, avoiding bottlenecks for AI training.
Intelligent Data Management
  • Snapshots, tiering and deduplication ensure efficient and reliable storage.
  • A unified namespace provides consistent access across all nodes.
Enterprise Integration
  • Seamless compatibility with Kubernetes, APIs and enterprise identity systems.
  • Real-time monitoring and analytics maintain predictable performance.

Virtualtek’s AI Storage Expertise with StorONE and Open-E Partnerships

AI storage deployment requires deep understanding of both storage architecture and machine learning workloads – expertise rarely found in traditional IT integrators. Virtualtek combines certified partnerships with StorONE’s enterprise storage platform and Open-E’s software-defined storage solutions to deliver purpose-built AI data architectures.

Our storage specialists perform comprehensive workload analysis, design optimal storage tiers, and integrate high-performance arrays with your GIGAPOD clusters. We ensure storage performance scales with your AI infrastructure growth while maintaining data integrity and regulatory compliance across European markets.

Key advantages

  • StorONE Partnership: Enterprise-grade storage platforms optimized for AI workloads
  • Open-E Expertise: Flexible software-defined storage for diverse AI requirements
  • Performance Validation: Storage architectures tested with actual AI training workloads
  • Seamless GIGAPOD Integration: Pre-validated connectivity with GPU cluster infrastructure
  • European Data Compliance: GDPR-ready storage with local data residency options
Design Your AI Storage Architecture

Partner

of Medium Business Success

AI Infrastructure & Virtualization Experts

Specialized in:
– AI Infrastructure (Official Gigabyte Partner)
– Virtualization (VMware Expert + Official Vates MSP)
– Enterprise Storage (Open-e, StorONE, Infortrend, AIC)
– Professional Training (training.virtualtek.io)

Discuss Your Infrastructure Requirements

Contact Info.

Offices.

  • Belgium & France

Headquarter.

  • Ruelle des colons, 14 - 4252 OMAL - BELGIUM

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