Most enterprise AI solutions are in fact a front end placed on a US cloud API — the question, the document and the customer data all leave the company. With us the deployment model is your decision, not ours.
The entire system runs on the company's own infrastructure, with an open-weight language model (for example Llama or Mistral) on your own GPU server. It works on a closed network too. Not a single byte leaves the company — not the question, not the answer, not the document.
A dedicated virtual environment (VMware, Kubernetes or a dedicated EU private cloud) under the company's control. A good choice when there is no in-house GPU capacity but the data must not go to a public cloud.
Sensitive data and processing stay on site, less critical components run in an EU cloud. We draw the line together — based on a data asset map, not on guesswork.
Which one is right for you? This is not a matter of belief but of assessment: two weeks of reviewing your data protection and infrastructure situation will tell.
For enterprise AI this is the most important question, and most vendors do not answer it. We do:
The employee's question reaches the system over an encrypted channel (TLS 1.3).
The system retrieves the relevant sources from the company's own knowledge base — by permission: everyone only receives what they would be allowed to see anyway.
The language model runs in the location matching the chosen deployment model — on the company's own server in the on-premise case.
Every question and answer pair is logged: timestamp, user, sources used. Auditable, traceable, and it never leaves the system.
The model does not learn from your data. We commit to this contractually, and with on-premise deployment it is architecturally guaranteed: the model never reaches the outside world.
In 2026 the AI Act is no longer future tense. For every deployment we produce the system's risk classification documentation and supply what is needed to meet the transparency obligations (Article 50): the user knows they are talking to an AI, and answers are traceable with source references.
Internal enterprise assistant use cases typically fall into the limited-risk category — but we do not simply assert this, we derive it in documented form, use case by use case. If your legal team wants to go deeper, we are glad to sit down with them. This is a conversation we seek out, not one we avoid.
We know that at your company a rollout starts with a questionnaire. Good news: for us that is not an obstacle, it is home ground.
