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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. 🙌
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About Feedback Intelligence Jira Automation on Product Hunt
“Turn customer conversations into actionable product feedback”
Feedback Intelligence Jira Automation was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #158 on the daily leaderboard. 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.
Feedback Intelligence Jira Automation was featured in Productivity (659.9k followers), Artificial Intelligence (477.8k followers) and Side Project (5.5k followers) on Product Hunt. Together, these topics include over 278.7k products, making this a competitive space to launch in.
Who hunted Feedback Intelligence Jira Automation?
Feedback Intelligence Jira Automation was hunted by Nidhi Sehwag. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Feedback Intelligence Jira Automation stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Nidhi Sehwag