AI & Big Data Infrastructure

Enterprise infrastructure for AI workloads, GPU compute, scalable storage, analytics and data-intensive business environments.

Infrastructure for Modern AI Workloads

TMC Technology supplies enterprise server and storage platforms designed to support AI inference, GPU acceleration, big data analytics, virtualisation and high-performance compute environments.

Built around trusted Supermicro infrastructure, NVIDIA accelerated computing and scalable storage technologies, our solutions help organisations deploy reliable, high-performance platforms for demanding workloads.

Infrastructure Solutions

GPU Compute

AI-ready GPU platforms for inference, accelerated compute, rendering and enterprise workloads.

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AI Storage

High-speed NVMe and enterprise storage infrastructure for large datasets and analytics pipelines.

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Big Data Platforms

Scalable infrastructure for analytics, data processing, HPC and business-critical applications.

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Edge AI

Compact and distributed compute platforms for edge inference and remote deployment environments.

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Designed for Data-Driven Organisations

AI Inference

Deploy infrastructure for real-time AI decision-making and accelerated workloads.

Private AI

Support secure internal AI environments with enterprise-grade compute and storage.

Analytics

Process large datasets with high-performance server and storage architecture.

HPC

Infrastructure for simulation, modelling, research and compute-intensive workloads.

Why TMC Technology?

  • UK-based server and storage infrastructure specialist
  • Supermicro, NVIDIA, Areca and Chenbro expertise
  • GPU, NVMe and enterprise compute platform knowledge
  • Custom configuration and product sourcing support
  • Infrastructure guidance for AI, virtualisation, HPC and analytics workloads
  • Support for modern data-intensive enterprise environments

Planning an AI Infrastructure Project?

Speak to TMC Technology about GPU servers, NVMe storage, enterprise compute and scalable infrastructure for AI and big data workloads.

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