Dear Confluence Admins,
I’m curious to learn how you’re using external AI tools to manage, maintain, and enhance your Confluence Data Center instance.
To clarify — I’m not referring to Rovo / Atlassian AI, but rather tools like Claude Code and similar agentic or code‑assistant solutions.
I’d love to hear how others are experimenting with AI across operational tasks, content governance, automation, developer workflows, or anything else you’ve tried.
Here are a couple of examples we are currently exploring:
May this thread grow into a productive discussion that sparks fresh ideas and brings real value to our Confluence DC environments — at least until we will all be nudged toward the cloud 😉.
Hi @david cockrell ,
I mainly work with Atlassian Cloud, so I have not personally seen many examples of organisations combining Confluence Data Center with external, agentic AI tools yet. These examples you've mentioned are quite interesting 👀
I do work quite a lot with organisations in the financial sector, though. While this is not necessarily related to their Atlassian environments (they've mainly moved to cloud), many banks still operate a range of on-premises systems and have developed their own internal AI platforms or assistants. This allows them to benefit from AI while keeping data, access, auditing and processing within the regulatory, security and internal-policy boundaries they need to follow. 📜
I imagine a similar approach could become increasingly relevant for Confluence Data Center customers: internally hosted or tightly controlled AI models that can support content governance, classification, plugin development, upgrades and administration without exposing sensitive Confluence data to public AI services. 🤔
I would like to hear real-life stories (if anyone can and is willing to share them)...
Cheers,
Tobi
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