AI Agents for Confluence: Atlassian Rovo and Connected Agents

Rovo is Atlassian's AI layer, and in Confluence it answers questions using your pages, drafts and summarizes content, and searches across Confluence, Jira, and connected tools. Ask it where the onboarding runbook lives or to summarize a long space, and it responds from your actual wiki rather than the open web. For teams already standardized on Confluence, that in-context search and drafting is the headline benefit, and it comes bundled with the plan.

The mechanic to plan around is credits. Every licensed seat earns a monthly pool, 25 on Standard, 70 on Premium, 150 on Enterprise, and it resets each month with no rollover. Rovo Chat and Rovo Agent requests cost 10 credits each, Deep Research costs 100, and plain Rovo Search is free. Do the arithmetic on Standard: 25 credits is about two agent interactions per person per month before the included allowance runs out. Atlassian is not charging for overage as of mid-2026 and has committed to 90 days notice plus an explicit opt-in before it starts, so today heavy use is throttled by the pool rather than billed, but either way the pool caps how much agent work each seat can do. Rovo also stays inside your Atlassian data, which is exactly what you want for wiki search and exactly the limit when you need answers pushed elsewhere.

A marketplace agent connects to Confluence through its API with scoped, revocable access and treats your wiki as a knowledge source it can use all day. It indexes the spaces you allow, answers questions from your real pages with a citation back to the source, drafts and updates documentation, and flags pages that have gone stale. The difference that matters for a busy team is where the answers land: the agent can deliver them in Slack, inside a help desk reply, or as a CRM note, so the knowledge in Confluence reaches the people who need it without anyone opening the wiki. And because it runs on a flat subscription, none of that spends a credit or risks an overage.

This is where a connected agent complements Rovo rather than replacing the wiki. Rovo is great for a person searching Confluence directly; the connected agent is built to answer from that knowledge at volume and route it across systems. Teams often pair it with enterprise search that finds any answer at work so the agent can draw on documents beyond Confluence, and with a connected AI agent for customer service so support replies are grounded in the same source of truth. If your team also runs on Jira, our AI agents for Jira page covers the same Rovo credit model on the tracker side.

A knowledge agent is only as good as the pages it reads and the permissions you set, so scope it deliberately. You choose which spaces the agent can index, and whether it can edit and publish pages or only draft changes for a person to approve. For anything customer-facing, keep the agent answering from approved spaces and citing the source page, so a reviewer can check where an answer came from. Restrict edit rights to the spaces a team truly owns, and let the agent propose rather than publish where accuracy matters most.

Every action the agent takes is logged, so you can see which page answered a question and what the agent changed. Every agent listed on the marketplace is reviewed and security-scanned before it goes live, and you can see exactly what it does and which permissions it needs before you connect it to a live Confluence instance. Compare the knowledge and support agents side by side in the AI agent store, and read how to vet an AI agent before you grant it access to your wiki.