Does Confluence Have AI Agents? Rovo, Credits, and the Limits (2026)

Yes, Confluence has AI agents. Atlassian builds them in through Rovo, its AI layer that answers questions from your wiki pages, drafts and summarizes content, and searches across your Atlassian tools. Rovo comes bundled with paid Confluence plans, but it runs on a per-seat credit pool that limits how much agent work each person can do, so it is worth understanding before you rely on it. This guide covers what Rovo does, how the credits actually work, and when a connected agent from outside Atlassian is the better fit.

If you would rather compare the built-in and connected options directly, our AI agents for Confluence page lays them side by side. Here is the detail.

What Rovo does in Confluence

Rovo turns Confluence from a place you store documents into a place you can ask questions. It answers from your actual pages, so you can ask where the onboarding runbook lives or what the refund policy says and get a real answer with a source, instead of scrolling search results. It drafts new pages and summarizes long ones, and it searches across Confluence, Jira, and connected tools in one query. You can also create Rovo Agents, small purpose-built assistants for specific jobs like triaging documentation requests or drafting release notes.

For a team already standardized on Confluence, that in-context search and drafting is a genuine upgrade, and it comes at no separate license charge because it is bundled with the plan. The catch is not the capability. It is the meter.

How Rovo credits actually work

Every licensed Confluence seat earns a monthly pool of Rovo credits that resets with no rollover: 25 credits on Standard, 70 on Premium, and 150 on Enterprise. The number that matters is what each action costs. A Rovo Chat or Rovo Agent request costs 10 credits. Rovo Search is free. Deep Research costs 100 credits.

Do the arithmetic on the Standard plan. Twenty-five credits at 10 credits per agent request is about two agent interactions per person, per month, before the included pool is spent. Premium's 70 credits gets you roughly seven, and Enterprise's 150 about fifteen. A single Deep Research request, at 100 credits, costs more than a Standard seat gets in an entire month. For occasional questions that is plenty. For a team that wants an agent answering from the wiki all day, it is a hard ceiling.

As of mid-2026, Atlassian is not billing for usage above the included pool, and it has committed to giving at least 90 days notice and requiring an explicit opt-in before it starts charging for overage. So today, heavy use is throttled by the credit pool rather than billed as a surprise. Either way, the pool is the thing that caps how much agent work each seat can do, and that is the number to plan your rollout around.

The other limit: Rovo stays inside Atlassian

Rovo is scoped to your Atlassian data and surfaces. That is exactly what you want when a person is searching Confluence directly. It becomes a limit the moment you need the wiki's knowledge somewhere else: answering a customer in your help desk, replying in Slack, or dropping context into a CRM note. Rovo answers inside the Atlassian tools; it does not run your support queue or your sales chat from the knowledge in Confluence.

Connecting your Atlassian knowledge to the rest of your stack is a common need, and it is usually solved with a tool that connects your apps, APIs, and databases so the same source of truth reaches every system, or with an agent that reads Confluence and acts elsewhere.

When a connected agent is the better fit

A third-party agent from the marketplace connects to Confluence through its API and treats the wiki as a knowledge source it can use all day, without spending credits. It indexes the spaces you allow, answers questions from your real pages with a citation to the source, and, crucially, delivers those answers where your team works: in Slack, in a help desk reply, in a CRM note. Because it runs on a flat subscription from $29 a month rather than a per-request credit pool, high-volume knowledge work does not deplete an allowance or risk an overage.

The two are complementary. Rovo is the fit when your team searches and drafts inside Confluence and the credit pool covers your usage. A connected agent is the fit when you want answers at volume, when the credit pool would run out, or when the knowledge needs to reach other systems. Plenty of teams keep Rovo for in-wiki work and add a connected agent for the cross-system, high-volume jobs.

The short answer

Confluence has AI agents through Atlassian Rovo, bundled with paid plans and capable of answering from your wiki, drafting, and searching across Atlassian tools. The limit is the per-seat credit pool (25 on Standard, 70 on Premium, 150 on Enterprise, at 10 credits per agent request) and the fact that Rovo stays inside Atlassian. For high-volume knowledge work or answers that need to reach Slack, your help desk, or CRM, a flat-rate connected agent is the better tool. You can browse ready-made AI agents and compare both approaches on our AI agents for Confluence page.