Provide a managed audit in which trained testers run standardized multi-day conversation scenarios across defined user personas. Each engagement produces annotated transcripts, reproducible failure cases, severity ratings, and recommendations covering memory, conversational style, emotional responsiveness, safety escalation, and mode continuity. The operation can later be productized with a reusable scenario library and automated transcript scoring while retaining human review for nuanced interactions.

AI assistants are increasingly used as companions, while users are comparing products on long-term memory and how naturally they handle difficult emotions. These qualities require repeated longitudinal testing that ordinary launch-day evaluations miss.