A complete guide to using an AI agent with Confluence in 2025

Let me guess: your team spends hours documenting everything in Confluence. Product specs, how-to guides, internal processes, it’s all in there, meant to be your single source of truth. But when a customer has an urgent question, your support agents are still left scrambling, digging through pages and old Slack threads to piece together an answer. The knowledge exists, but finding it in the heat of the moment is another story.

What if you could fix that? An AI agent can turn your Confluence from a quiet library into an active assistant that serves up instant, accurate answers right where your team works.

This guide will walk you through the options for bringing an AI agent to your Confluence setup. We’ll look at Atlassian’s own AI, the build-it-yourself route, and third-party tools to help you figure out what makes the most sense for your team.

What is an AI agent for Confluence?

Simply put, an AI agent for Confluence is a smart tool that plugs into your knowledge base to understand all your company’s information. It then uses that knowledge to answer questions and help with tasks for employees or customers, whenever they need it.

So, how does it actually work? Most AI agents today use a technology called Retrieval-Augmented Generation (RAG). Instead of just guessing or pulling from the public internet, the AI first scans your own Confluence pages to find the most relevant info. Then, it uses that specific material to put together a precise, helpful answer.

Basically, it’s all about making your team’s shared knowledge easy to grab and use on the fly. This cuts down on the time everyone wastes searching for stuff and helps your teams solve problems much faster.

The ‘built-in’ approach: Using Atlassian Intelligence

It’s worth mentioning that Confluence comes with its own native AI, which can be a perfectly fine starting point for some teams. Let’s take a look at what it can do and where it might leave you wanting more.

What is Atlassian Intelligence?

Atlassian Intelligence is a set of AI features built right into the Atlassian product family, including Confluence. These features are mostly designed to help people who are already working inside the platform.

Here’s a quick rundown of what it offers:

• Content generation: It can help you draft a new page, brainstorm some ideas, or tweak the tone of your writing with a simple prompt.

• Summarization: It can boil down long pages or messy comment threads into key points so you can get up to speed quickly.

• Automation: You can create simple rules, like archiving old pages, just by describing what you want in plain English.

• AI search: You can ask questions directly in Confluence and get answers pulled from your pages.

Atlassian Intelligence is really built for the folks who live in Confluence all day, content writers, project managers, and product teams who need a hand with documentation.

Limitations of the native AI

While it’s handy for managing internal docs, Atlassian Intelligence runs into trouble when you look at the day-to-day needs of a modern support team.

The biggest issue is that it’s trapped inside the Atlassian world. Let’s be real, your company’s most useful knowledge, the stuff that actually solves customer problems, is scattered all over the place. It’s in old support tickets in Zendesk, saved replies in Freshdesk, and troubleshooting guides in Google Docs. Atlassian’s AI can’t see or learn from any of that.

This video provides an introduction to the features of Atlassian Intelligence within Confluence Cloud.

This creates a few headaches:

• It doesn’t get the world of customer support. The AI isn’t built for the little details of customer service. It can’t pick up your brand’s voice from past conversations or do important things like look up an order status or route a ticket correctly.

• There’s no good way to test it. You can’t run a simulation to see how the AI will handle real customer questions before you flip the switch. There’s no way to check how it would have performed on last month’s tickets, which makes it a bit of a gamble for customer-facing tasks.

• It keeps your knowledge trapped. By only using what’s in Confluence, it actually reinforces the information silos that slow your team down.

So while Atlassian Intelligence is a decent tool for internal work, support teams need an AI that can pull together all your company knowledge, no matter where it is.

The ‘build-your-own’ approach: Custom development

If you have a team of engineers with time to spare, building a custom AI agent from scratch is always an option. You can use frameworks like LangChain and connect to vector databases to create something totally unique.

The clear advantage here is complete control. You can build the agent exactly how you want it, tailored perfectly to your team’s way of working. But this path has some pretty serious drawbacks.

• Time and cost: This isn’t a weekend project. Building a custom AI agent can take a dedicated engineering team months of work, with costs easily running into the tens or even hundreds of thousands of dollars.

• Complexity and upkeep: You need people who are experts in AI, data engineering, and security. And it’s not something you can just set up and forget about. The system needs constant care, updates, and tweaks to keep it working well.

For most companies, the money, time, and hassle just don’t add up, especially when other platforms can give you more power with way less effort.

The integration approach: A smarter AI agent

This brings us to the third option, and for most teams, the most practical one: an integrated AI agent platform. This route gives you the power of a custom-built solution without the headaches by connecting Confluence to all your other tools.

This is where a platform like eesel AI comes in. It’s designed from the ground up to break down the knowledge silos that frustrate support teams, using Confluence as just one source in a much bigger, unified brain.

This infographic illustrates how an integrated AI agent for Confluence like eesel AI connects to various knowledge sources beyond just Confluence to provide comprehensive answers.

How eesel AI overcomes common limitations

eesel AI was built to tackle the problems you run into with both native and DIY agents, giving you a tool that’s powerful but still surprisingly easy to manage.

Here’s how it works:

• Bring all your knowledge together in a snap

  Unlike Atlassian’s walled-off AI, eesel AI connects to your help desk, chat tools like Slack, and other sources like Google Docs or Notion. Even better, it trains on your past support tickets to learn your brand voice and common customer issues right away, giving it a depth of support context a generic agent just can’t get.

• Get started in minutes, not months

  You can forget about long, drawn-out development projects. eesel AI is designed to be completely self-serve. You connect your tools with one-click integrations and can have your AI agent up and running in minutes, often without ever needing to talk to a salesperson or write a line of code.

• Full control and testing you can trust

  This is where dedicated platforms really start to shine. Before you go live, eesel AI’s Simulation Mode lets you test your agent on thousands of your past tickets. You can see exactly how it would have responded, get solid forecasts on its resolution rate, and tweak its behavior in a totally risk-free environment.

A screenshot of the eesel AI platform’s Simulation Mode, where you can test the AI agent for Confluence on past tickets before going live.

You also get fine-grained control. With **Selective Automation**, you decide which tickets the AI should handle. You could start with simple, repetitive questions and have it [pass everything else to a human](https://www.eesel.ai/blog/bot-or-human). You can even set it up to perform specific actions, like tagging tickets in your help desk or [looking up order details in Shopify](https://www.eesel.ai/blog/top-shopify-ai-apps-to-automate-support-sales-and-more) through an API call.  

Pricing explained

When you’re thinking about a native AI tool, it’s important to look at the real cost. Atlassian’s AI features are not part of the Free or Standard plans. You only get them if you upgrade to the Premium or Enterprise tiers.

This means to get access to Atlassian Intelligence, your entire team’s Confluence plan has to be upgraded, which can add up quickly.

Plan	Price (per user/month)	Atlassian Intelligence
Free	$0	❌ No
Standard	$5.16	❌ No
Premium	$9.73	✅ Yes
Enterprise	Contact Sales	✅ Yes

This per-user pricing model can get expensive. In contrast, platforms like eesel AI have straightforward, predictable pricing based on usage (how many AI interactions you have per month), not how many people are on your team. For a lot of teams, this ends up being a much more affordable way to add powerful AI to their support workflow.

Choosing the right AI agent for Confluence

So, what’s the best move for your team? Let’s do a quick recap of the options:

1. Built-in (Atlassian Intelligence): A decent starting point for internal documentation and workflows, but it’s too disconnected and limited for teams that talk to customers all day.

2. Build-your-own: Gives you total control but is incredibly expensive, complicated, and time-consuming for almost everyone.

3. Integrated (eesel AI): The sweet spot. It’s powerful, quick to set up, and connects all your knowledge to deliver a genuinely intelligent and automated support experience.

While Confluence is a great place to store information, you unlock its true potential when you connect it to the rest of your tools. An integrated AI agent doesn’t just search Confluence; it turns your company’s entire collective knowledge into a tool that solves customer problems in seconds.

Give your team the knowledge they need instantly

Ready to break down your knowledge silos and give your support team an AI that works across all your apps?

Try eesel AI for free and see how it can turn your Confluence knowledge into instant, automated resolutions.