Private AI on your own enterprise data

Private AI is a complete AI stack that runs entirely inside an environment you control. The language model, retrieval over your documents, access management and logging — all of it sits on infrastructure you operate, or on a dedicated private cloud inside the EU. None of your data ever leaves that environment.

This is fundamentally different from public AI such as ChatGPT, Gemini or Copilot. With those tools, every question, every document and every customer name is sent to a US-based provider. Private AI removes that dependency. You keep control over your intellectual property, your customer data, and your compliance posture.

• The AI model runs on infrastructure you operate or inside the EU.
• Your data is never used to train public foundation models.
• Every data flow is auditable — you see exactly what happens where.
• No vendor lock-in to a single US hyperscaler.
• GDPR- and EU AI Act-compliant by default, without legal workarounds.
• Operates on your own documents, not a generic web corpus.

Adoption of private AI is accelerating sharply in 2026. Research from Deloitte and KPMG shows that an increasing share of European and US enterprises are pulling back from public AI tools. The reasons keep recurring: data-leak risk, mounting compliance pressure from the EU AI Act, and the loss of control over intellectual property.

• No more data leakage to US vendors or third parties.
• Full compliance with GDPR, NIS2 and the EU AI Act.
• Your intellectual property stays inside your organisation.
• Higher answer quality, because the model works on your own documents.
• Independence from Big Tech price hikes or policy changes.
• A defensible position toward regulators, customers and auditors.

Private AI uses a technique called Retrieval-Augmented Generation (RAG). Rather than retraining the model on your data — which is expensive and risky — the system searches your documents at the moment a question is asked. It retrieves the relevant passages, feeds them to the language model, and generates an answer with source attribution.

That gives you three major advantages. One: your data stays where it is — it is never baked into the model. Two: you can add or remove documents in real time, no retraining required. Three: every answer cites its source, so outputs are verifiable and explainable.

• RAG pipeline with hybrid search across your own documents.
• Source attribution on every answer — explainable and auditable.
• Real-time document add or remove without retraining.
• Role-based access — users only see what they are allowed to see.
• Full audit trail of every question and every response.

Research from national cybersecurity centres and Capgemini shows that public AI tools have become one of the fastest-growing categories of enterprise security risk. Employees routinely paste customer data, source code or contract details into ChatGPT or Copilot. That data then travels to servers outside the EU and can end up in training corpora.

• Shadow AI: employees use public tools without IT visibility.
• Data leakage via prompts containing customer names, IDs or contract values.
• No audit trail of what happens to the data once it is sent.
• Indefensible toward auditors, DPOs and regulators.
• Exposure to EU AI Act penalties (up to 7% of global revenue).

Private AI is no longer reserved for global enterprises. Thanks to open-weight models such as Mistral, a complete private AI stack is now viable for mid-market organisations as well. We design and run the environment, manage the model, and handle the updates. Your team brings the use cases.

Amaii is a European private AI specialist. We design, host and operate private AI platforms for organisations that refuse to compromise on privacy, control or compliance. No black box, no hidden sub-processors, no US dependency. Just a working system that delivers measurable value.