Your Trusted UK Cloud & Dedicated Server Partner Since 2006
Your Trusted UK Cloud & Dedicated Server Partner Since 2006
Powerful dedicated servers with NVIDIA GPUs optimised for AI training, machine learning workloads, and neural network inference. Deploy your AI projects with enterprise-grade infrastructure designed for maximum computational performance.
AI-Optimised Computing Infrastructure
Every component of our AI servers is engineered for machine learning workloads, from NVIDIA GPUs to high-speed interconnects, ensuring optimal performance for training and inference tasks.
Our servers feature the latest NVIDIA RTX and A-series GPUs with CUDA cores, Tensor cores, and massive GPU memory designed specifically for AI training, deep learning inference, and complex neural network operations.
NVIDIA RTX 4090, A6000, and H100 GPUs with up to 80GB VRAM for large model training
CUDA, cuDNN, and TensorRT optimization for PyTorch, TensorFlow, and JAX frameworks
NVLink and high-bandwidth GPU interconnects for multi-GPU training and scaling
Faster training times compared to CPU-only systems with our GPU-accelerated infrastructure
System memory capacity for handling massive datasets and model parameters
Ultra-fast NVMe SSD storage for rapid dataset loading and model checkpointing
High-speed network connectivity for distributed training and data transfer
Our AI servers feature enterprise-grade hardware optimised for the demanding computational requirements of machine learning workloads, with high-bandwidth memory, fast storage, and powerful CPUs.
Intel Xeon or AMD EPYC processors with high core counts for parallel processing tasks
Up to 2TB DDR5 ECC memory for handling large datasets and complex model architectures
High-speed NVMe SSD arrays with up to 100TB capacity for dataset storage and model artifacts
Our servers come pre-configured with essential AI development tools and frameworks, providing you with a complete machine learning environment ready for immediate deployment of your AI projects.
PyTorch, TensorFlow, JAX, and Hugging Face transformers with optimised GPU drivers
Jupyter Lab, Python ecosystem, CUDA toolkit, and containerisation with Docker/Kubernetes
Multi-node training capabilities with InfiniBand networking and MPI communication
Expert support for GPU drivers, ML frameworks, and distributed training configurations
Optimised hardware and software stack for machine learning workloads
Enterprise GPUs, high-bandwidth memory, and ultra-fast storage for AI training
GPU-Accelerated AI & Machine Learning Servers
Choose from our high-performance GPU servers designed for AI training, inference, and machine learning research, from individual projects to enterprise-scale deployments.
Individual AI projects
From
£149/mo
Research & development
From
£299/mo
Most popular choice
From
£699/mo
Our AI servers include advanced security features with encrypted storage, secure SSH access, network isolation, and compliance-ready configurations for handling sensitive datasets and proprietary models.
Scale from single-GPU prototypes to multi-node distributed training with auto-scaling capabilities, load balancing, and seamless integration with MLOps pipelines for production AI deployments.
Common Questions About AI & ML Servers
Our AI servers feature the latest NVIDIA GPUs with CUDA cores and Tensor cores specifically designed for parallel processing and matrix operations essential in machine learning. We include pre-installed ML frameworks like PyTorch and TensorFlow, optimised CUDA drivers, high-bandwidth memory for handling large datasets, and NVMe storage for fast data loading. The servers also support distributed training with high-speed interconnects and come with containerisation tools for MLOps workflows.
Yes, we provide comprehensive AI migration services handled by machine learning engineers and DevOps specialists. Our migration process includes transferring your datasets, model checkpoints, training scripts, and environment configurations while maintaining data integrity and model performance. We handle framework compatibility, GPU driver optimization, and distributed training setup. The migration typically takes 24-48 hours for standard setups, and we provide thorough testing to ensure your models train and inference correctly on our infrastructure.
We offer 24/7/365 expert support from certified AI infrastructure specialists and machine learning engineers who understand the complexities of GPU computing and distributed training. Our support includes CUDA driver updates, ML framework optimization, distributed training configuration, performance tuning, and emergency response for critical training jobs. We provide proactive monitoring of GPU utilization, memory usage, and training metrics, automated backups of models and datasets, and can assist with hyperparameter tuning, model deployment, and MLOps pipeline setup.