Put AI agents to work on your content
A chat assistant can describe the change you want to a diagram or a changelog. It cannot make it. Scoped AI agents can — and the difference is one install, not a project.
Why this matters across Confluence and Jira
Teams do not have an AI problem with answering questions — Confluence and Jira chat already do that. They have a problem with *acting*. Ask a general assistant to update an architecture diagram and you get a paragraph describing what you could draw; ask it which pages hold stale onboarding boards and you get nothing, because it has no index of your content and no ability to change it. The work still lands on a human with the canvas open. A scoped agent closes that gap — but only for the content type it was built for, which is why the interesting question is not "should we use AI" but "which content type is worth handing to one."
Content goes stale because maintenance costs more than attention
The architecture board three sprints out of date is not neglected, it is rationally deprioritized: every update means opening an editor, finding the right element, and moving it. That is a few minutes of fiddly work against an uncertain payoff, so it never wins against a real ticket. Every stale diagram is a small rational decision repeated by everyone who could have fixed it.
A description of a change is not a change
General-purpose assistants are fluent about what an update *should* contain and have no ability to apply it to a page, an issue, or a canvas. The gap between the suggestion and the saved artifact is exactly where the manual work lives. An agent that can write the change closes it; one that can only narrate it moves the work rather than removing it.
Scope beats generality
"Draw the deployment flow" is an unambiguous instruction for an agent that only knows how to draw flows. Hand the same sentence to a general assistant and you get clarification questions and prose. Narrow scope is what makes the agent fast and predictable — and it is why an agent for one content type can be worth installing when a general AI assistant is already available to you.
Agents should widen your options, not close them
A good agent writes the same artifact the manual editor writes, so anything it produces stays hand-editable and nothing you tuned by hand gets quietly redrawn. That is the property to check before installing anything: if the agent output could not be fixed by hand afterwards, it is a black box, and black boxes are the reason content rots in the first place.
The approach that works
Picking and adopting a scoped agent comes down to six checks. None of them require writing code, and all of them can be answered by installing the app and trying it on a real page — which is why every app below is free for up to 10 users.
- 1
Name the content type you actually maintain
Not the content type you care about — the one you keep having to update. Most teams maintain far less than they think: one architecture board, one runbook, one recurring report. Write that list down before you look at any product, because the value of a scoped agent is entirely determined by whether its content type is on your maintenance rotation. An agent for a content type you never touch is pure novelty.
- 2
Check it writes native content, not an export
The single most important check. If the agent produces a picture, an external link, or a blob in a vendor store, you have not fixed maintenance — you have moved the staleness somewhere less visible, and search, permissions, and export all break. What you want is the agent writing the same on-platform artifact the editor writes, so search still finds it, permissions still apply, and history still tracks it.
- 3
Start with the verbs that replace an edit, not a decision
Rename this shape, regroup these boxes, restyle this element, convert this block — these replace mechanical edits and are where an agent is reliable from day one. Choose the overall composition, the visual treatment, and the structure of a document: those are judgment calls, and handing them to an agent early is how you end up with confident output nobody can defend. Let the agent do the renaming; keep the redesign.
- 4
Verify the permission behaviour before you trust it with sensitive content
Ask directly whether queries run as the asking user, and test it against content the requester should not see. An agent that runs with elevated access is a security review, not a feature — and it will be discovered by your security team, not by you. This is also why on-platform storage matters twice over: it is what makes the permission question answerable at all.
- 5
Confirm the manual path is unchanged
Install the app and check that the classic editor still does everything it did, that your existing content still opens, and that something you tuned by hand is not redrawn on the next agent run. An agent that replaces the editor is not an agent feature, it is a migration. The good version is the one where chat and editor write the same thing and neither can lock the other out.
- 6
Let them accumulate in the same conversation
The compounding effect comes from chaining, not from any single prompt: create the thing, then correct it, then restyle it, then find the four other pages that need the same treatment. Agents work in the chat surface you already have open on the page, so keeping the loop inside one page beats exporting to some other tool and re-importing the result.
This solution is for you if…
- Teams whose architecture boards, runbooks, or onboarding maps are months out of date
- Engineers and architects who would rather describe a diagram change than drag eleven boxes into alignment
- Tech leads and PMs who keep asking "which pages still have the old version?" and get a shrug
- Anyone who has asked a chat assistant to update a page and received a paragraph instead of a change
- Jira teams who need to answer "what changed on this issue?" without knowing which field to open
- Admins evaluating whether an agent app is worth installing, and on what evidence
Our apps that solve this
Every app is free for up to 10 users on the Atlassian Marketplace. Pick the one that fits your workflow, or combine them.
ConfluenceMermaid Plus Diagrams & AI Agent for Confluence
Chat to create, read, update and convert Mermaid diagrams in Confluence — powered by a Rovo AI agent
ConfluenceExcalidraw Plus Whiteboards & AI Agent for Confluence
Chat to create, edit, search and convert Excalidraw whiteboards in Confluence — powered by a Rovo AI agent
JiraIssue History Agent for Jira
See who changed what on any Jira issue — field-level history, word-level diffs, and a Rovo agent that answers what changed
Read the guides
Frequently asked questions
It is an assistant scoped to one content type — diagrams, whiteboards, issue history — that can act on your content rather than only describe it. You ask in the chat already open on the page; it creates, edits, or converts the artifact and saves it to the page. Because it is scoped, "draw the deployment flow" is an unambiguous instruction rather than a vague one it has to interpret.
Why teams choose NGPILOT
Free for up to 10 users
Every app is free for small teams, with the full trial Atlassian provides for larger ones.
Native Forge apps
Built on Atlassian Forge, running entirely on Atlassian Cloud infrastructure.
Your data stays in your instance
No content is sent to our servers — processing happens inside your Confluence or Jira.
Verified Marketplace vendor
NGPILOT apps are listed, reviewed, and maintained on the Atlassian Marketplace.
Ready to try it?
Every app is free for up to 10 users. Install in a couple of clicks.