AI over your data, on your premises
Private AI & RAG
We build AI that knows your documents, contracts and know-how — while no data ever leaves your infrastructure unless you want it to.
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The problem we solve
Banking, healthcare, manufacturing and legal professions hold data they must not or do not want to send to public AI services. Yet exactly there, AI over internal knowledge would save the most time. Most off-the-shelf tools don't resolve this conflict.
Typical scenarios
- chat over documents from drives, Confluence, SharePoint or a DMS
- search across contracts, directives and technical documentation
- RAG that respects permissions — everyone sees only what they may
- fully local operation on your hardware (GPU server, own datacentre)
- hybrid mode — sensitive data locally, generic tasks in the cloud
Security and operations
On-premise deployment means documents, indexes and models run on your side. Access follows your identities (SSO/AD) and every query is auditable. We operate our own GPU infrastructure, so we know what local operation takes in practice.
How we work together
We start with analysis and a solution proposal with a quotation, continue with architecture and staged development, and finish with acceptance and deployment — which we then operate long-term. The whole process is described on the home page.
Technologies
Local models via Ollama/vLLM (Llama, Mistral, Qwen), the Qdrant vector database, custom embeddings and pipelines. The cloud variant uses OpenAI with an EU region.
- Ollama
- Llama
- Mistral
- Qdrant
Related projects
Frequently asked questions
How powerful does our hardware need to be?
For a team of up to dozens of users, a single GPU server is enough. We help with sizing and procurement — we run such infrastructure ourselves.
Can it respect document permissions?
Yes — the RAG index carries permission information, and answers are composed only from sources the person asking may access.
How is the solution kept up to date?
Documents are indexed continuously (folder watching, DMS connectors). We update the model and pipeline as part of long-term support.
Ready to start a new project?
Tell us about your project — we reply within one business day.
Discuss your project