Feedback Intelligence Jira Automation - Turn customer conversations into actionable product feedback

Feedback gets scattered across interviews, meetings, transcripts and spreadsheets. The context behind it often gets lost before it becomes a product decision. Feedback Intelligence turns conversations into structured feedback, preserving the source, user signal and domain context. Review and enrich it, create a draft ticket, and push approved feedback to Jira. Built for domain-heavy B2B products where the “why” behind a request matters as much as the request itself.

Hey Product Hunt 👋 I built Feedback Intelligence after noticing a recurring problem in B2B product work: valuable feedback often lives inside conversations, but the context behind it gets lost by the time it becomes a Jira ticket. This matters even more in domain-heavy products, where a user's comment can contain important workflow and domain knowledge that doesn't fit neatly into a feature request. So I built a small workflow to connect: **Conversation → Feedback → Review → Jira** I built and deployed the MVP in 3 days using OpenCode, Supabase, Vercel and free-tier tools. I intentionally kept a human review step instead of fully automating ticket creation, and added the option for users to bring their own model API key. This is still an early product, and that's why I'm launching it here. I'd love to know: • Would this solve a real problem for you? • What would you want it to do next? • What part of the workflow would you automate differently? Try it, break it, and tell me what you think. 🙌

Feedback Intelligence Jira Automation - Turn customer conversations into actionable product feedback

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