Your guide to finding the best Confluence agent in 2025

So, you’re using Confluence. It starts out great, right? A few pages for a project plan, a document for the new HR policy. But then you blink, and it’s grown into a sprawling digital library with thousands of documents.

Suddenly, finding the right information feels like a full-time job. Your team starts spending more time digging through page trees than actually working. You see the same questions pop up in Slack over and over, even though you know the answer is documented somewhere in that maze.

This is exactly the problem a Confluence agent is built to solve. Think of it as an intelligent layer you put on top of your knowledge base. It lets your team ask questions in plain English and get instant, accurate answers. Instead of searching, they just ask.

This guide will walk you through what a Confluence agent is, compare the different routes you can take (from native tools to custom builds and third-party platforms), and help you figure out which one actually makes sense for your business.

What is a Confluence agent?

A Confluence agent is an AI-powered app that connects to your Confluence instance, reads everything, and understands it. Its main job is to let people have a conversation with your knowledge base, usually through a chat window inside the tools they already use every day, like Slack or Microsoft Teams.

How does it work? Most of these agents use a technology called Retrieval-Augmented Generation (RAG). That might sound complicated, but the idea is simple. When you ask a question, the agent first scans all your Confluence pages to find the most relevant bits of information. Then, it hands just those snippets to a large language model (the same kind of tech behind ChatGPT) and tells it to write a clear answer using only that information.

It’s like having an expert on your company’s internal knowledge who has perfect memory and can respond instantly.

The result is that your static, hard-to-navigate wiki becomes a dynamic resource that people actually want to use. This one change can save countless hours, cut down on repetitive shoulder taps, and just make everyone’s workday a little less frustrating.

The usual Confluence agent suspects: Native AI vs. a DIY build

Before looking at dedicated platforms, most teams think about two options: using Atlassian’s built-in AI or trying to build an agent themselves. Both sound good on paper, but they come with some serious trade-offs.

Atlassian’s native Confluence agent: Rovo agents

Atlassian has its own AI called Rovo, which is baked directly into Confluence. It can search your spaces, summarize pages, and handle some basic tasks. It’s a convenient place to start, but you might hit a wall with it pretty quickly.

• It only plays in Atlassian’s sandbox. Rovo is built for the Atlassian ecosystem. But what if your company knowledge also lives in Google Docs, Notion, or old support tickets? Rovo can’t see any of that. This creates blind spots, meaning your agent will often give incomplete answers because it doesn’t have the full story.

• It can be a pain to manage. While you can configure Rovo agents, getting them to do exactly what you want is another story. Customizing their behavior means diving into Atlassian’s developer platform, a process that’s often way too technical for the people who actually manage the knowledge (like your HR or IT teams). You’re left with a system that feels powerful in theory but is clunky in practice.

• The pricing gets expensive, fast. Rovo isn’t something you can buy on its own. It’s bundled into the more expensive Confluence plans. So, if you want the AI, you have to upgrade your entire subscription for every single user. That bill can climb quickly, especially if only a small part of your team really needs the AI features.

The DIY approach: Building your own Confluence agent

For companies with a lot of engineers, building a custom Confluence agent can seem like the best path. You get complete control, right? You can connect to the Confluence API, set up your own vector database, and manage the AI models yourself. It’s an ambitious idea, but as many a developer guide will show you, it’s a huge project with some real downsides.

• It’s a bigger, more expensive project than you think. This isn’t a weekend hackathon. Building and maintaining a custom AI agent requires a dedicated team of specialized developers. The costs for infrastructure, APIs, and salaries add up, and that’s before you even think about the ongoing work needed to keep it running.

• There’s no user-friendly dashboard. Custom-built tools rarely come with a nice interface. This means your non-technical folks can’t update knowledge sources, adjust the AI’s personality, or check its performance. Every little tweak becomes a ticket for the engineering team, creating a brand new bottleneck.

• Security and scaling are all on you. With a DIY solution, you’re responsible for everything. As your company grows and your knowledge base gets bigger, you’ll have to constantly pour more time and money into the infrastructure just to keep up.

What to look for in a powerful Confluence agent

A dedicated third-party platform often hits the sweet spot. It gives you the power of a custom solution without the headache of building and maintaining it yourself. Here’s what you should be looking for.

1. It should have an easy, self-serve setup

The best tools are the ones you can start using immediately. You shouldn’t have to schedule a demo, talk to a salesperson for a week, or hire a developer just to get started. Look for a platform that’s genuinely self-serve, with one-click integrations that connect to your tools in minutes, not weeks.

For example, with a platform like eesel AI, you can connect your Confluence knowledge base and launch a fully working AI agent in Slack in less than five minutes, all by yourself.

A flowchart showing the simple, self-serve implementation process for an effective Confluence agent like eesel AI.

2. It should connect to all your knowledge, not just Confluence

Your company’s brain isn’t just in one place. It’s spread across Google Docs, Notion, PDFs, websites, and thousands of old support tickets and Slack threads. An agent that only reads from Confluence will always be missing key context.

This is where a dedicated platform really shines. A tool like eesel AI is built to unify all your scattered knowledge into one reliable brain for your agent to draw from.

A screenshot of the eesel AI platform displaying the wide range of integrations available for a Confluence agent, connecting all knowledge sources.

3. You should have full control over its behavior

A one-size-fits-all AI doesn’t cut it. Every team works differently, and you need fine-grained control over how your agent behaves. Look for a simple prompt editor that lets you define the AI’s tone of voice and set clear rules for when it should answer and when it should pass the question to a human.

You should also be able to create "scoped" agents. For instance, maybe you want an HR bot that only pulls answers from the HR space in Confluence, or a legal bot that only uses approved legal docs. eesel AI lets you set up these kinds of rules right from the dashboard, no code needed.

An image of the eesel AI dashboard where users can customize the behavior and set specific rules for their Confluence agent.

4. You should be able to test it before going live

How can you trust an AI before you let it talk to your team? You need a safe place to test it out. A good simulation mode will let you run the agent on past questions or support tickets to see exactly how it would have responded. This gives you a clear idea of its performance and the confidence to roll it out. This is a core feature of eesel AI, allowing you to fine-tune your agent in a sandbox environment before your team ever interacts with it.

A screenshot of the eesel AI simulation mode, where you can test the performance of your Confluence agent before deployment.

Top use cases for a Confluence agent

Once you have a smart agent running, you can start solving real problems across the company. Here are a few of the most common ways teams use them.

Answering internal IT and HR questions

An AI agent can be the first line of defense for your internal support teams. It can instantly handle the most common employee questions, like "How do I set up my VPN?" or "What’s our parental leave policy?" by pulling answers straight from your Confluence docs. This frees up your IT and HR folks from answering the same things over and over, so they can focus on trickier issues. With eesel AI’s Internal Chat, you can put this agent right in Slack or MS Teams, where your employees are already working.

A screenshot showing the eesel AI Confluence agent answering an internal support question directly within Slack.

Helping out developers and product teams

Engineers and product managers live in documentation. Instead of bugging a senior developer to ask about an API endpoint, they can just ask the agent. It can pull up code snippets, link to the right technical docs, and summarize project specs on the spot, helping everyone stay on the same page.

Onboarding new hires

The first few weeks at a new job are a firehose of information and questions. A Confluence agent can be a huge help for new hires, answering all the little things they might feel awkward asking a teammate, from "Where are the brand guidelines?" to "How do I submit an expense report?" It helps them get up to speed faster and ensures they get consistent, correct info from your official knowledge base.

This video demonstrates how a Confluence AI agent can automatically resolve user requests within Slack, showcasing a key use case.

The Confluence agent price tag: Confluence AI pricing vs. dedicated agents

As we touched on earlier, Atlassian bundles its AI features into its pricier plans and uses a credit-based system. This means you’re not only paying more per user for the plan itself, but your costs can also be unpredictable. Here’s a quick look at Confluence’s pricing.

Plan	Price (Annual)	Key AI Feature	Limitation
Free	$0	None	N/A
Standard	$5.16/user/month	Rovo Search, Chat, and Agents	25 AI credits/user/month
Premium	$9.73/user/month	Rovo Search, Chat, and Agents	70 AI credits/user/month
Enterprise	Contact Sales	Rovo Search, Chat, and Agents	150 AI credits/user/month

This model can be a bit of a headache. AI credits can get used up fast, and if you have a busy month, you could face unexpected charges or find your AI features turned off.

A dedicated platform usually offers a more straightforward price. For example, eesel AI’s pricing is based on a set number of AI interactions per month. There are no weird credit systems or hidden fees. You know exactly what you’re paying, which makes budgeting and scaling much simpler.

Don’t settle for a limited Confluence agent

Look, Confluence is a great place to store your company’s knowledge. But relying on its native AI can leave you with a solution that’s incomplete and inflexible. And trying to build your own agent is usually far more complex and costly than it first appears.

A dedicated, third-party platform gives you the best of both worlds: power, flexibility, and simplicity. The right Confluence agent should do more than just read your wiki; it should connect to all your company knowledge, give you full control over its behavior, and be easy enough for anyone to manage.

Your knowledge deserves a smarter Confluence agent

Ready to get more out of your Confluence documentation? eesel AI connects to Confluence and all your other tools in minutes, delivering instant, accurate answers to your team right where they work.

Start your free trial today and see how easy it is to set up a truly effective Confluence agent.