EU production server
Dedicated VPS · France · Ubuntu 24.04 · Docker
- Traefik
- Coolify
- Forgejo
- Grafana + Prometheus
- Ghost
- Astro
- Rybbit
- Postiz
- n8n
- agno
- Twenty CRM
EU-RESIDENT · OPEN SOURCE · SELF-HOSTED
Your most sensitive data. Finally usable.
AI that runs inside your infrastructure — so the contracts, case files, and financial records you could never send to a cloud API become the material your firm actually works with. Open source, EU-resident, and yours to keep.
Running this business today
- vLLM / llama.cpp
- Qdrant
- ComfyUI
- n8n
- agno
- Coolify
- Traefik
- Forgejo
- Grafana + Prometheus
- Ghost
- Astro
- Rybbit
- Postiz
- Twenty CRM
// THE PROBLEM
The data with the most to gain is the data you can't send anywhere.
Financial contracts, client communications, case files, medical records. The material where AI would save the most hours is precisely the material that can't go near an external API.
GDPR, the EU AI Act, and your own security policy all land in the same place: sensitive workloads belong inside your infrastructure. The question is no longer whether — it's how, and who builds it.
Traditional API call
CLIENT_DATA = { sensitiveData };
response = await openAI . chat . completions . create({
messages: [{ role: { user } , content: CLIENT_DATA }]
});
// Data leaves your infrastructure
// Compliance violation risk
// ✓ Zero data egress · EU sovereign · GDPR compliant
// WHAT WE DO
Five services, usually in this order.
Data foundations
Most AI projects fail on the data, not the model. We connect the systems you already run, clean and structure what's in them, and make the result queryable — so the insight you're missing becomes reachable before anyone trains anything.
Learn more →Private LLM deployment
Your own language models on your own hardware. Draft, summarise, and search across material that was never allowed near a public API.
Learn more →AI workflow automation
Document intake, approval routing, internal knowledge search. The repetitive work that eats billable hours, handled on your own systems.
Learn more →AI security & compliance
A structured audit against the EU AI Act, GDPR, and your internal policies — including the classification work: which data may leave your infrastructure, which may not, and the evidence for both. Risk model and remediation plan you can hand to your board.
Learn more →Generative AI pipelines
Image, video, and content generation running locally. Brand-consistent output at scale, with no per-generation cost.
Learn more → // PROOF
We run exactly what we recommend.
Intraion runs on the same architecture we build for clients: two machines, self-hosted, entirely EU-resident. Not a reference diagram — the production system this business depends on.
Two machines. Nothing leaves them.
EU PERIMETER
Local AI cluster
Mini-PC cluster · Portugal · self-managed
- vLLM / llama.cpp
- Qdrant
- ComfyUI
Deliberately modest hardware — the same starting point we recommend to firms who assume private AI needs a datacentre.
Nothing inside this boundary sends data outside it.
External AI APIs
Never called. No key issued, no route out.
- Monthly SaaS cost
- €0
- Data leaves the EU
- Never
- Vendor lock-in
- None
- Open source
- 100%
// PROCESS
From first call to production in weeks.
Audit
We map your current tools, data flows, and compliance constraints. 90-minute call.
Design
We architect the right stack — model selection, hardware sizing, integration points. Nothing proprietary.
Deploy
We install, configure, and test inside your infrastructure. You keep the keys.
Ownership
Full documentation, staff training, and support only if you want it. You can run it without us — that's the point.
// FROM THE BLOG
We build in public.
The Engineer in the Machine: Why AI Agents Do Not Replace Developers
The prevailing narrative in boardrooms across the EU is that the cost of software development is about to collapse. The logic seems sound: if a Large Language Model (LLM) can write a function, a class, or an entire module in seconds, the need for a human to type those characters into a text editor disappears. The conclusion drawn is often that the headcount of the engineering team can be reduced proportionally to the speed of the AI. This is a category error. It confuses the act of typing code
7 min read Read more →
The Hidden Cost of AI Hesitation
A senior associate in a mid-sized legal firm spends six hours on a Friday afternoon reviewing a set of discovery documents. The task is precise: identify every instance where a specific liability clause was modified across forty different versions of a contract. It is tedious, manual work that consumes a significant portion of the billable day. The associate knows that a large language model could perform this extraction in seconds. However, the firm’s policy is absolute: no client data is to
8 min read Read more →
Intelligence within your walls.
A free 90-minute readiness session. We map your use case, assess your infrastructure, and tell you honestly what's worth doing — no commitment.
Book a free session