AI is useful when a clear use case, suitable data, and verifiable outcomes come together. We therefore start with the process and its risks—not with a model or the current hype.
Privacy and control by design
Before implementation, we clarify data classes, legal basis, retention, provider access, model training, logging, and human oversight. Depending on sensitivity, we compare European hosting, Microsoft options, private endpoints, and locally operated open-source models.
Focused use cases
Suitable scenarios include internal knowledge search, document classification, support assistance, structured extraction, and traceable process automation. Sensitive decisions remain reviewable and receive clear escalation paths.
- Use-case, value, and risk assessment
- Privacy-conscious architecture and data minimization
- Private RAG and knowledge solutions
- Local open-source models and controlled cloud services
- Evaluation, guardrails, monitoring, and human approval