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Your AI. Your data. Hosted in the EU.
Service — Private AI & Self-Hosted LLMs
Language models that run in your own infrastructure or with an EU hosting provider, so sensitive data does not leave your control. We select, deploy and operate open models such as Llama, Mistral and Qwen, connected to your systems and secured for production.
Private AI, production-ready.
Private AI, production-ready.
What we build
Self-hosted LLM deployment
Open-weight models served with vLLM, Ollama or TGI on your servers, in your cloud account or with an EU GPU provider.
Model selection & benchmarking
Comparing open models on your tasks and languages, balancing quality, speed and hardware cost.
Private RAG & knowledge assistants
Assistants over your internal documents where embeddings, index and model all stay in your environment.
Fine-tuning & adaptation
LoRA fine-tuning on your domain data when prompting and retrieval are not enough, without your data training anyone else’s model.
Stack
Open models, open tooling.
Data residency is an architecture decision.
Control by design
Where a model runs determines where your prompts, documents and answers are processed. We make that decision explicit: what stays on your infrastructure, what may use an EU provider, and how every request is logged and protected.
From requirement to running model.
How we work
[Build]
[01]
Requirements & data classificationWhich data is involved, where may it be processed, and which quality and latency does the use case need?
[02]
Model & hosting choiceWe benchmark candidate models and recommend on-premise, private cloud or EU hosting with a cost estimate.
[Deliver]
[03]
Deploy & integrateModel serving, API gateway, monitoring and integration into your applications and identity provider.
[04]
Operate & updateUpdates to new model versions, evaluation before each switch, and capacity planning as usage grows.
Further reading
Go deeper on this topic.
Self-Hosted LLMs in 2026: Private AI for EU Firms
Article: when self-hosted models are the better choice.
Why We Host Everything in the EU
Article: our reasons for EU hosting and data sovereignty.
Embeddings & semantic search
Vector search, hybrid retrieval and RAG pipelines.
Cloud & DevOps
EU infrastructure, Kubernetes and monitoring.
FAQ
Private AI, clearly answered.
A self-hosted large language model runs on infrastructure you control, such as your own servers or a dedicated cloud account, instead of being called through a public AI provider’s API. Prompts and data are processed inside that environment.
For many business tasks such as classification, extraction, summarisation and RAG, current open models perform well. For complex reasoning, commercial models are often still ahead. We benchmark on your tasks so the choice is based on evidence.
It helps by keeping processing in an environment you control, but compliance also depends on purpose, legal basis, access control, retention and documentation. We design the technical side and work with your data protection officer on the rest.
It depends on the model size and request volume. Smaller quantised models can run on a single GPU; larger models need more memory or several GPUs. We size the setup and compare it with EU GPU hosting before you invest.
Not automatically. At low volume, APIs are usually cheaper. Self-hosting becomes attractive with steady high volume or strict data requirements. We calculate both options for your use case.
Yes. A routing layer can send sensitive requests to the private model and less sensitive ones to a commercial API, behind one internal endpoint.
Want AI without sending data outside?
Tell us which data and use case you have in mind. We outline a private setup with hosting options and an honest cost comparison.
Get in Touch
Book an intro call.
Tell us about your project — we'll get back within 24 hours with a tailored proposal. No fluff, no boilerplate.
Pick a slot that suits you — or use the form. We reply within 24 hours on working days.
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