Building a product feedback loop with Tinybird MCP and LLM

In an effort to streamline and prioritize customer support issues, a system was developed using Plain webhooks, Tinybird, and an AI agent to automate the process of generating a weekly digest for the product team. This system captures events from Plain and pushes them into a Tinybird datasource, where the data is processed and transformed into a coherent format using materialized views. Conversations are aggregated and analyzed, with the results made accessible through a secured HTTP endpoint. A cron job further enhances the data by generating GPT summaries, which are then compiled into a Slack channel report for easy viewing. The integration of these technologies enables efficient data ingestion, real-time processing, and secure delivery of insights, allowing teams to focus on the most pressing customer issues.

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