AI Feedback Management Video | explainer video made with ngram

About the video

This explainer video was made with ngram to explain how fivetran's product team moved from manual, scattered customer feedback handling to an ai-powered feedback intelligence system. the video walks through centralizing feedback data from zendesk, salesforce, and jira into a unified warehouse, then layering ai agents on top of it. it details a three-agent architecture: an assessment agent that evaluates requests against product principles, a browser agent that researches external signals and competitor information, and a synthesis agent that combines findings into feasibility reports with effort estimates. it also covers how the system generates personalized customer responses in minutes instead of hours, shifting pm time from manual research toward strategic decisions. the explainer is aimed at product managers, product marketing teams, and others interested in scaling feedback operations, giving a concrete look at the technical stack and workflow behind fivetran's implementation, including how feasibility and business impact get assessed automatically rather than through ad hoc manual review.