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On-Premise AI

AI Servers & Infrastructure

Run your own AI models on your own hardware. Complete data sovereignty, zero cloud dependency and predictable costs at scale. Your data never leaves your premises.

Design Your AI Server Why On-Premise?
On-Premise AI

Your AI, Your Hardware, Your Rules

We design, build and deploy on-premise AI server infrastructure tailored to your workload requirements. From single GPU workstations to multi-node clusters, we handle the full lifecycle.

Our engineers assess your AI use cases, recommend the optimal hardware configuration, install and configure the software stack, and provide ongoing management and support. You get the power of enterprise AI without the complexity.

  • Full hardware specification and procurement
  • Rack installation, networking and power provisioning
  • OS, driver and CUDA stack configuration
  • AI framework deployment (PyTorch, TensorFlow, vLLM, Ollama)
  • Monitoring, alerting and remote management
GPU server infrastructure in a data centre rack
GPU Infrastructure

Purpose-Built for AI Workloads

We specify and configure GPU servers optimised for inference, training and fine-tuning across a range of budgets and performance requirements.

Inference Servers

Optimised for running trained models at scale. Low-latency responses for chatbots, document processing and real-time analytics. NVIDIA RTX and Tesla GPU configurations.

Training Clusters

High-memory multi-GPU configurations for model training and fine-tuning. NVLink interconnects, high-bandwidth storage and thermal management for sustained compute loads.

Edge AI

Compact, low-power AI compute for edge deployment. NVIDIA Jetson and Intel NUC-based solutions for manufacturing floors, retail locations and remote sites.

AI language model interface representing private LLM hosting
Private LLM Hosting

Run Your Own AI Language Models

Deploy state-of-the-art large language models on your own infrastructure. Llama, Mistral, Mixtral, Phi and other open-source models running privately within your network.

  • Deploy Llama 3, Mistral, Mixtral, Phi-3 and more
  • ChatGPT-like interfaces for your entire organisation
  • RAG (Retrieval Augmented Generation) with your company data
  • Fine-tune models on your domain-specific knowledge
  • API endpoints compatible with OpenAI format
  • No per-token costs -- unlimited usage at fixed cost
  • Complete conversation privacy -- nothing logged externally
Data Sovereignty

GDPR Compliance by Design

When you process data through cloud AI services, that data leaves your control. With on-premise AI, every byte stays within your network perimeter. This is not just a preference -- for many regulated industries, it is a requirement.

  • Zero data transmission to external servers
  • Full compliance with GDPR Article 5 data minimisation
  • Meets NHS, legal and financial sector data handling requirements
  • Complete audit trail of all AI interactions
  • Air-gapped deployment options for maximum security
  • Data processing impact assessments included
Data protection and GDPR compliance shield
Fine-Tuning Services

AI Models Trained on Your Knowledge

Generic models give generic answers. We fine-tune open-source models on your company's data, documentation and domain expertise to create AI that truly understands your business.

Domain Adaptation

Train models to understand your industry terminology, processes and knowledge base. Legal, medical, engineering, financial -- whatever your domain, we make the AI speak your language.

Custom Assistants

Build AI assistants that know your products, policies and procedures inside out. Answer customer queries, support internal teams and automate routine knowledge work with accuracy.

Continuous Learning

Models that improve over time. We implement feedback loops and periodic retraining pipelines so your AI gets smarter as your business evolves and new data becomes available.

The Case for Local AI

Why On-Premise Beats Cloud AI

Cloud AI has its place, but for many organisations, on-premise infrastructure delivers clear advantages.

Privacy

Your data never leaves your network. No third-party processing, no data sharing agreements, no risk of training data leaking into someone else's model. True privacy, not just a promise.

Speed

No internet round-trip. Local inference delivers sub-second responses for most queries. Critical for real-time applications, interactive tools and high-throughput processing pipelines.

Cost at Scale

Cloud API costs scale linearly with usage. On-premise costs are fixed after initial investment. For high-volume workloads, local AI pays for itself within months and continues to save.

Availability

No dependency on cloud provider uptime or internet connectivity. Your AI runs 24/7 regardless of external service outages, rate limits or API deprecations.

Control

Choose your models, set your own content policies, update on your schedule and customise behaviour without restrictions. No vendor lock-in, no surprise policy changes.

Compliance

Simplify regulatory compliance by keeping all AI processing within your controlled environment. Easier auditing, clearer data lineage and straightforward impact assessments.

Hardware Recommendations

Right-Sized for Your Needs

We recommend hardware based on your workload, budget and growth plans. Here are typical configurations.

Starter

From £5,000

one-time hardware cost

  • Single NVIDIA RTX 4090 (24GB VRAM)
  • Runs 7B-13B parameter models
  • Ideal for small team AI assistant
  • Document processing and chatbots
  • Up to 20 concurrent users
  • Compact tower or 2U rackmount
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Most Popular

Professional

From £15,000

one-time hardware cost

  • Dual NVIDIA RTX 5090 or A6000 GPUs
  • Runs 30B-70B parameter models
  • Enterprise-grade AI capabilities
  • RAG with large document sets
  • Up to 100 concurrent users
  • 4U rackmount with redundant PSU
  • Remote management (IPMI/iDRAC)
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Enterprise

From £40,000

one-time hardware cost

  • 4-8x NVIDIA H100 or A100 GPUs
  • Runs 70B-405B parameter models
  • Multi-model serving and training
  • NVLink/NVSwitch interconnects
  • Unlimited concurrent users
  • High-availability clustering
  • Dedicated management and SLA
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Ongoing Management

We Manage Your AI Infrastructure

Deploying hardware is just the beginning. We provide ongoing management to keep your AI systems running at peak performance.

Monitoring

24/7 GPU health, temperature, memory and throughput monitoring with proactive alerting.

Updates

Regular driver, CUDA toolkit, framework and model updates tested and deployed safely.

Security

Network isolation, access controls, encryption at rest and in transit, and regular security audits.

Scaling

As your needs grow, we plan and execute hardware upgrades and cluster expansion seamlessly.

Build Your Private AI Infrastructure

Take control of your AI strategy with on-premise infrastructure. Our team will design the perfect solution for your needs, budget and compliance requirements.

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