Choose a bounded, recurring problem
Processing one document type, searching a defined knowledge base or producing a specific summary is a stronger starting point than making everything intelligent. Record sample coverage, current task time and acceptance criteria so results can be compared.
Define access and confidentiality before the model
Which data may enter the system and who may see the output? Are external services permitted? Retention, source permissions and event logging need clear rules. Model selection follows these decisions.
Evaluate quality with real examples
Separate typical, difficult and exceptional examples. Extraction errors, unsupported answers and failure to recognise missing information are different failure modes. The system should identify authorised sources and make its limitations clear when evidence is insufficient.
Turn a pilot into a usable product
User roles, review steps, error states and integration matter as much as the model. Begin with a small user group, record outcomes and feedback, then expand after evaluation.