AI tied to a business need
We connect AI services to existing applications for internal document access, recurring information requests and text processing. AI is not required for every process; accuracy, cost and data sensitivity determine suitability.
RAG and enterprise search
Retrieval-Augmented Generation lets a model use selected document passages when composing an answer. Source freshness, user permissions and citations are designed together. Model answers are not assumed to be universally correct.
Security and evaluation
Provider selection, data transfer and retention are reviewed against organizational requirements. Boundaries address prompt injection, unauthorized document access and personal data risks. Assistants that perform actions need human approval and audit records.
Pilot and operation
Representative evaluation set → limited pilot → quality and cost assessment → controlled adoption. We measure answer quality, unanswered questions and latency, repeating evaluation after model or source changes.
Application scenarios
Combine camera analysis and sensor data with location information for remote monitoring and fill-level maps.
Pilot boundaries and evaluation
Start with a document collection or a limited workflow. Define tests for retrieval, permissions and answer correctness. Admitting missing evidence and requesting human approval for high-impact actions are deliberate design choices. No accuracy percentage is promised without relevant data and evaluation.
Explore the topic
Define the scope together
Start with the current process, system inventory and intended outputs. Acceptance scenarios and delivery responsibilities are documented. Discuss your project.
The AI-generated cover illustrates the service topic; it is not a customer project photograph.