AI Agents That Make Confluence Findable Again
AI agents that search Confluence in plain language, summarize long pages, draft new docs from your templates, and answer team questions grounded in your real documentation.
5× faster than searching the wiki
Teams asking their AgentTeams agent instead of searching Confluence find answers in seconds.
Confluence has the answer. Nobody can find it.
Years of pages, dozens of spaces, and a search bar that never quite returns the page you remember writing.
Average time to find a doc
Pages exist. Search returns sixty results. The right one is on page three. By the time you find it, you've forgotten why you needed it.
Of pages haven't been touched in a year
Stale runbooks, outdated policies, half-finished docs that nobody flagged or removed.
Of questions are repeats
The same five questions get asked in Slack every week. The answer's in Confluence. Asking is faster than searching, so people ask.
How it works with Confluence
Three steps to an AI team member that works alongside you in Confluence.
Connect Confluence
Connect your Confluence Cloud workspace via OAuth. The agent appears as a user with whatever permissions you grant.
Pick the spaces
Choose which spaces the agent can read and write. Start with one or two; expand once you see the quality.
Let it work
Ask it questions, have it summarize, let it draft. The agent gets sharper the more your team interacts with it.
Everything you need for Confluence that gets used
From search to summarization to drafting, your AI agent makes the wiki valuable instead of dusty.
Plain-language search
Ask in natural language; the agent searches across spaces by meaning, not keyword. Returns the right page, not twenty maybes.
Page summarization
Long architectural docs and meeting notes get summarized on demand. Skim a page in fifteen seconds, not fifteen minutes.
Template-driven drafting
Drafts new pages following your team's templates: design docs, RFCs, meeting notes, runbooks. Right structure, right metadata, right space.
Comment management
Reads and responds to page comments. Surfaces unanswered ones before they go stale. Keeps doc reviews moving.
Space-aware navigation
Understands your space structure, engineering, ops, customer success, and routes questions to the right space, not a global keyword soup.
Permission-aware
Respects Confluence's existing space and page permissions. The agent only sees what its user is allowed to see, same as a human teammate.
What teams use it for
Concrete examples of Confluence agents in production today.
Engineering wiki for support
Support escalates a ticket: 'Why does the webhook fail with 422 on these payloads?' The agent searches the engineering Confluence space, finds the relevant API doc, and surfaces the answer with a link to the source page. Support stops needing engineering for documented things.
Onboarding new hires
New hires ask the agent setup questions for their first week. It walks them through the docs, points to the runbooks they need, and answers grounded in what the team has actually written down, instead of by-DM tribal knowledge.
Decision history queries
'Why did we pick PostgreSQL over MySQL?' The agent finds the RFC from two years ago, summarizes the decision, and links the source. Past context becomes accessible instead of buried.
Frequently asked questions
Things people commonly ask before deploying an AgentTeams agent in Confluence.
Does it work with Confluence Cloud, Server, or Data Center?
Confluence Cloud is fully supported via OAuth. Server and Data Center work for read operations through API tokens, with some write features depending on your version. Most modern teams are on Cloud and that's the smoothest path.
Can the agent write to Confluence or only read?
Both. The agent creates pages from templates, edits existing ones, posts comments, and updates labels. You decide which actions need approval and which it can do autonomously.
How does it handle our existing space and page permissions?
It respects them exactly. The agent has its own Confluence user; you give it access to whatever spaces you'd give a human teammate. It can never see content you haven't shared with it.
Will it confuse old or outdated pages with current ones?
It uses recency, version history, and structural cues to weight current docs over stale ones. You can also tag pages explicitly as 'archive' or 'current' in directives, and it'll prefer the current set.
Can it draft using our team's templates?
Yes. Point it at your existing templates (design docs, RFCs, meeting notes) and it'll match the structure, fields, and metadata. New pages get filed in the right space with the right labels applied.
Ready for an AI teammate in Confluence?
See how AgentTeams agents work alongside your team in Confluence , no engineering required, live in under an hour.
Or sign up for updates