Use cases

Hosting matched to your workload

Dedicated, EU-sovereign hosting matched to what you run — from AI/ML training and GPU compute to databases, streaming, and email infrastructure. Sized to your workload, with honest guidance on where we fit.

AI & GPU compute

AI & ML training AI and ML training needs GPUs with enough memory for your models, fast interconnect to scale across them, and storage that can feed them without bottlenecking. Dedicated GPU servers suit sustained training better than on-demand cloud, and EU-hosted hardware keeps training data under European jurisdiction.
AI inference AI inference — serving trained models in production — is bound by latency and throughput rather than raw training power. It needs enough memory to hold the model, the ability to scale with demand, and high availability. Steady production load favours dedicated servers, and EU hosting keeps live user data under European jurisdiction.
LLM hosting Hosting an LLM means running a very large model in production, which is dominated by memory — the model weights plus the KV cache that grows with context length and concurrency. Large models often need high-memory or multiple GPUs. Self-hosting keeps prompts and outputs private and, in the EU, under European jurisdiction.
Deep learning Deep learning trains and runs neural networks, which are computationally intensive and GPU-accelerated. Beyond GPUs, it needs a working software stack — frameworks like PyTorch and TensorFlow with matching drivers — and infrastructure spanning experimentation, training, and inference. Dedicated GPU servers suit sustained deep-learning work, hosted in the EU for data sovereignty.
Machine learning pipelines A machine-learning pipeline is the end-to-end workflow that turns data into a deployed model and keeps it current — ingestion, processing, training, deployment, and monitoring. It needs mixed compute (CPU for data, GPU for training), orchestration to coordinate the stages, and storage for data flowing between them. EU hosting keeps the whole pipeline's data sovereign.
ML platforms An ML platform is the shared, self-hosted infrastructure an organisation's teams run their machine-learning work on — a common pool of GPU compute, environments, storage, and orchestration serving many projects and pipelines. Sharing resources improves utilisation and cost, and self-hosting in the EU keeps the whole organisation's ML data under European jurisdiction.

HPC & scientific compute

Finance & fintech

Databases

Big data & analytics

Web & apps

DevOps & CI/CD

Virtualisation

Streaming & media

Gaming

CDN & delivery

VPN & networking

Don't see your exact workload?

We host dedicated, EU-sovereign infrastructure across compute, storage, networking, and email. Tell us what you're running and we'll size it — or point you elsewhere if we're not the fit.

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