The ultimate guide to finding the right Confluence chatbot

Confluence is where all your company’s important knowledge is supposed to live. It’s a great spot for everything from HR policies to complex engineering roadmaps. But let’s be real. As your company grows, so does your Confluence space. Before you know it, it feels less like an organized library and more like a cluttered attic you’re scared to go into. Finding that one specific bit of info you need turns into a frustrating treasure hunt through endless pages and outdated search results.

Sound familiar?

If your team is spending more time searching for answers than actually working, you’re not alone. The built-in search function has its moments, but it often dumps a long list of pages on you, leaving you to do the heavy lifting of sifting through them all. This is exactly where a Confluence chatbot can help. Think of it as a smart assistant living right inside your wiki, ready to understand your questions and give you instant, clear answers pulled directly from your documentation.

This guide will walk you through the options out there, from Atlassian’s own AI to building one yourself, so you can figure out the best way to make your Confluence a knowledge hub that actually works for your team.

What is a Confluence chatbot?

A Confluence chatbot is an AI tool that connects to your Confluence spaces to answer questions conversationally. Instead of typing keywords into a search bar and getting a list of links, you can just ask a question in plain English, like, "What’s our policy on parental leave?" or "How do I set up my developer environment?" The chatbot digs up the right information and gives you a straight answer.

The tech behind this is called Retrieval-Augmented Generation (RAG). It sounds a bit technical, but the idea is pretty simple: the chatbot doesn’t just guess or make things up. It first retrieves the most relevant bits of text from your actual Confluence pages and then uses that information to generate a helpful, accurate answer. This keeps the AI grounded in your company’s specific knowledge, so you can actually trust its responses.

The perks are pretty obvious:

• Instant answers: It gets rid of the manual work of searching, clicking, and reading through long documents.

• More productive teams: Your team spends less time digging for information and more time on the work they were actually hired to do.

• Better use of docs: When information is easy to find, people are much more likely to use the documentation you’ve spent so much time creating.

• Fewer support tickets: Internal teams like IT, HR, and Ops can head off common questions before they even become support tickets.

Option 1: The native approach with Atlassian Intelligence (Rovo)

The most direct way to add AI to Confluence is by using the tool Atlassian built themselves. Atlassian Intelligence, powered by their AI engine called Rovo, is baked right into the platform.

What is Atlassian Intelligence?

Atlassian Intelligence is the brand name for the AI features you’ll see across all of Atlassian’s products, from Jira to Confluence. For Confluence, it can summarize long pages, help you write new content, and, most importantly, answer questions using the information in your spaces. It uses something Atlassian calls a "Teamwork Graph" to try and understand how people, projects, and documents are all connected, hoping to give you answers with more context.

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

Pros and cons of the native approach

On the surface, using the built-in tool seems like a no-brainer. But it’s not without its trade-offs.

Pros:

• Seamless integration: It’s already part of the Confluence interface. You don’t have to install or set up a third-party app.

• Ecosystem aware: In theory, it can pull context from your Jira tickets and other Atlassian products to improve its answers.

• Trusted provider: It’s made by Atlassian, which can make getting approval from security and legal a bit easier.

Cons:

• Stuck in the Atlassian ecosystem: This is the biggest catch. Your company’s knowledge isn’t just in Confluence. It’s in Google Docs, Slack threads, Notion pages, and your help desk. Atlassian’s AI can’t see any of that, so its answers will always be incomplete. It only knows what’s in its little bubble.

• Limited customization: You get very little say over the AI’s personality, how it acts when it can’t find an answer, or which specific pages it has access to. It’s pretty much a one-size-fits-all solution.

• Tied to expensive plans: The most useful AI features are only available on Atlassian’s pricier Premium and Enterprise plans. If you’re on a Standard plan, you get a tiny number of AI interactions each month that disappear quickly.

Atlassian Intelligence pricing

Rovo is included in Confluence Cloud plans, but how much you can actually use the AI depends on how much you pay. The free plan doesn’t include it, and the credits on the Standard plan can be used up in a flash. To really get what Atlassian’s AI has to offer, you’ll have to open up your wallet for an upgrade.

Option 2: The DIY approach

For companies with some engineering firepower, building a custom Confluence chatbot is another route. This path gives you a ton of flexibility but also comes with a whole lot of complexity.

What does a DIY approach involve?

Building your own chatbot from the ground up means you’re piecing together the entire system yourself. This usually means using open-source frameworks like LangChain to connect to the Confluence API, pull the text from your pages, turn that text into a format the AI can understand (called embeddings), and store it all in a special vector database. Then you have to connect all of that to a large language model (LLM) like GPT-4 and build a user interface for it. It’s a full-on development project.

The reality of the DIY approach

This approach gives you total control, but you have to be realistic about what it really takes.

Pros:

• Complete customization: You can design the chatbot to do exactly what you need, integrate it with any internal system, and meet any specific security rules you have.

• No subscription fees: You won’t be paying a monthly bill to another company, but you will be paying for infrastructure (hosting, API calls, etc.) and, of course, developer salaries.

Cons:

• It’s expensive and slow: This isn’t a weekend project. It takes a serious investment of time from skilled developers, not to mention the ongoing maintenance needed to keep it running.

• A long wait for results: It can easily take months of building, testing, and tweaking before you have a chatbot that’s reliable enough for your team to actually use.

• It’s complicated: You’re on the hook for everything: data security, managing API keys, making sure it runs fast, and checking that the AI gives accurate answers. It’s a lot to manage.

For most companies, the time and money needed to build a custom solution just don’t add up, especially when there are powerful, ready-made tools out there.

Option 3: The specialist approach

This brings us to our third option: using a specialized, third-party tool. This approach often hits the sweet spot, giving you the power and flexibility of a custom solution without the cost and headaches of building it from scratch.

Why choose a specialist tool?

Specialist tools are built to do one thing and do it incredibly well. Their whole reason for being is to make your company’s knowledge easy to access, so they usually come with more advanced features, better integrations, and a smoother user experience than a native add-on.

Unify all your knowledge, not just your wiki

The biggest weakness of native tools is that they only see a small piece of the puzzle. Real company knowledge is scattered all over the place. A tool like eesel AI was created to solve this exact problem. It connects to over 100 sources, including Confluence, Google Docs, Notion, Slack, and help desks like Zendesk.

This image shows how a specialist confluence chatbot can integrate with multiple applications to build a comprehensive knowledge base.::

This creates a single, unified brain for your entire company. When you ask a question, the chatbot can pull information from a Confluence page, a Google Doc, and a relevant Slack thread to give you a complete answer. It’s the difference between asking a librarian who has only read one shelf and asking one who has read the entire library.

Go live in minutes with a self-serve setup

Many enterprise AI tools force you into long sales calls and demos just to try the product. And building your own can take months. In contrast, eesel AI is designed to be totally self-serve. You can sign up, connect your Confluence account with a single click, and have a working chatbot ready for your team in minutes. No need to talk to a salesperson unless you really want to. It just works.

This workflow illustrates the simple, self-serve setup process for a dedicated confluence chatbot.::

Get total control and test with confidence

One of the biggest worries with any AI tool is having control over what it knows and says. This is another area where a specialist tool really delivers.

• Scoped Knowledge: With eesel AI, you can easily create different bots for different teams. For example, you can set up an "IT Help Bot" that only knows about your IT-related Confluence spaces and a separate "HR Policy Bot" that only has access to the HR space. This makes sure the answers are always relevant and that sensitive information doesn’t end up in the wrong hands.

This image displays the customization options for a confluence chatbot, allowing for scoped knowledge and specific rules.::

• Simulation Mode: How do you know if your chatbot is ready for your team? eesel AI has a powerful simulation mode that lets you test it on past questions or real-world scenarios before you roll it out. You can see exactly how it will respond and tweak its behavior, giving you complete confidence that it’s accurate, helpful, and safe to use. This is a crucial feature that you just don’t find in most other tools.

This screenshot shows the simulation mode of a confluence chatbot, where you can test its responses before deployment.::

Transparent and predictable pricing

Finally, you need a pricing model that doesn’t give you a headache. eesel AI offers clear, transparent plans without complicated per-answer fees. This means your bill won’t suddenly jump just because your team is having a busy month and using the chatbot a lot. The costs are predictable, and you can even start with a month-to-month plan, which is a low-risk way to prove its value.

Choosing the right Confluence chatbot for your team

So, what’s the best way to get a Confluence chatbot for your team? It really comes down to your needs and resources.

1. Native Atlassian AI: It’s convenient if your team lives and breathes Atlassian and you’re already paying for a high-tier plan. But it’s limited because it can’t see any knowledge outside of Confluence.

2. DIY Chatbot: This gives you ultimate control but costs a fortune in time, money, and engineering effort. It’s probably overkill unless you’re a huge company with very specific needs.

3. Specialist Tools: This is the balanced approach. It gives you way more power and flexibility than the native option, without the complexity of a DIY project.

For most teams, a specialist tool is the best of both worlds. A platform like eesel AI is a great choice for companies that need a powerful, easy-to-use chatbot that brings together all their knowledge, provides fine-grained control, and can be up and running in minutes, not months.

Ready to make your Confluence knowledge instantly accessible?

Stop wasting time searching and start getting answers. With eesel AI, you can launch a powerful chatbot trained on your Confluence spaces and other knowledge sources in under five minutes.

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