Create an AI-powered application that converts messy customer complaints into a structured, evidence-linked product improvement backlog.
Allow users to paste feedback from reviews, support tickets, surveys, and interview notes. Group similar complaints while preserving the original evidence behind every cluster.
The system should:
Separate symptoms, suspected causes, feature requests, and emotional reactions.
Detect duplicate reports without discarding unique details.
Identify affected user journeys and potential severity.
Generate testable problem statements and acceptance criteria.
Estimate priority using configurable impact, frequency, confidence, and implementation effort.
Flag contradictory feedback and cases where evidence is insufficient.
Produce a development-ready backlog with traceability to source comments.
Track whether shipped fixes actually reduce the reported problems.
Use fictional data for the initial demonstration. Do not treat the number of complaints as proof of market-wide demand. Allow human review before generating final backlog items, and make every AI-generated interpretation editable.
0 Comments