KodaSync - Turn user interview friction into ready-to-code Jira tickets

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Stop rewatching user interviews. KodaSync automatically extracts high-signal friction points from Fireflies or Fathom calls and turns them into ready-to-code Jira tickets—complete with user stories, acceptance criteria, and timestamped links to the evidence.

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Hey Product Hunt! 👋 I’m Sudheer, the maker behind KodaSync. As Product Managers, we speak to customers constantly. Our meeting recorders (like Fireflies or Fathom) are packed with gold—critical bugs, edge cases, and sudden "Aha!" moments. But let's be honest: who actually has the time to rewatch 10+ hours of video every week just to extract those insights and manually write tickets? This gap means brilliant user feedback gets lost, and engineering roadmaps shift back to "best guesses." I built KodaSync to bridge this exact divide between customer conversations and engineering resolution. Here’s the magic: 1. 🔄 Auto-Ingest: We connect with your existing meeting assistant. No extra bots to invite. 2. 🎯 Evidence-Based Insights: KodaSync extracts the exact high-signal friction points with precision timestamps. 3. ⚡ One-Click Engineering: Push a fully formatted ticket straight to Jira, complete with the User Story, Acceptance Criteria, and the exact timestamp link (the "receipts") so developers never say "cannot reproduce" again. We are launching our Founding Beta today! We are looking for 5 Product Managers to join us early, get free access for life, and help shape our feature roadmap. I'd love to hear from the community: - How do you currently bridge the gap between user calls and your engineering backlog? - What integrations would you like to see next (Linear, Asana, Zoom)? Check out the site at and let me know your thoughts in the comments! 🚀

honestly this looks super useful, saves a ton of manual note-taking after calls. one thing i'd love to see is a quick way to batch-confirm multiple generated tickets at once instead of approving them one by one, especially when you've got a bunch of similar feedback from different interviews that all map to the same underlying issue.

 Thanks for your feedback.