Issue Duplicate Finder for Jira – Official Support & Community Hub

[Alaeddine MELLITI _LOTUS INFO_]

Hi Atlassian Community,

We built Issue Duplicate Finder for Jira because we kept seeing the same problem across teams we worked with — engineers reopening tickets that already existed, support agents investigating incidents that had already been resolved, QA writing test cases that were already in the backlog.

It was costing teams real hours every week, and nobody had a simple fix for it inside Jira. So we built one.

The app detects duplicate and similar Jira issues in real time, the moment a new issue is created, it scans your backlog and surfaces the closest matches directly in the issue panel.

No manual searching. No context switching. Just an instant answer to "does this already exist?"

For teams managing SLA-sensitive queues, it means faster resolution by reusing what already worked. For leads watching capacity, it means less wasted sprint effort and lower support costs over time.

We've seen it make the biggest difference for:

• ITSM and support teams catching duplicate incidents before they breach SLA
• QA leads avoiding duplicate test cases in Xray or Zephyr
• Dev teams stopping redundant user stories from making it into a sprint
• Project managers keeping large Jira backlogs clean and navigable

This thread is our home base here on the community. Whether you have a question about setup, want to share how you're using it, or have an idea that would make it better, this is the right place.

If you're already using the app, we'd love to hear from you. What's working well? What would make it more valuable for your team?

🔗 https://marketplace.atlassian.com/apps/3082768133

[marc -Collabello--Phase Locked-]

Interesting, is this using AI to find the duplicate issues?

[Alaeddine MELLITI _LOTUS INFO_]

Hi Marc,

At the moment, Issue Duplicate Finder does not rely on AI or external LLMs. Instead, it uses similarity analysis on Jira issue data to identify potential duplicates quickly and consistently.

We chose this approach to keep the solution lightweight, predictable, and easy to adopt while avoiding the cost, latency, and data privacy considerations often associated with AI-based solutions.

That said, we're actively exploring AI-powered enhancements that could further improve duplicate detection accuracy and provide richer insights in future releases.

I'd be interested to hear what capabilities you would expect from an AI-assisted duplicate finder.

Thanks for your question!

Lotus Info