Artificial intelligence adds value when it solves a specific problem. We connect suitable models with your data and processes in a controlled, transparent way, with clearly defined boundaries.
Together, we identify tasks where AI can meaningfully support your staff: knowledge search, document processing, summaries or the analysis of technical information. Data quality, implementation effort and measurable success criteria determine the way forward.
We design local or privately operated language models and connect them to internal knowledge sources. Source-based answers, permissions and controlled data access are central to the design. Your requirements guide the choice between local infrastructure and external services.
We explore opportunities to detect anomalies, analyse measurement data and support maintenance and quality assurance. A pilot evaluates suitability under real operating conditions. Safety-critical decisions remain subject to defined human approval processes.
We integrate models into existing applications through clearly defined interfaces. Test cases, output evaluation, monitoring and documented limitations provide transparency. AI outputs are validated for their intended use rather than assumed to be error-free.
↗Prioritised AI use cases
↗Prototype & evaluation
↗Data & access concept
↗Integration & operational handover
The specific services and deliverables are tailored to your requirements and the agreed project scope.