Let’s be honest, most companies are sitting on a mountain of useful information. The catch? It’s scattered everywhere, buried in Slack DMs, living in random Google Docs, hidden in old support tickets, and locked away in the brains of your most senior teammates. When someone needs an answer, they’re usually stuck, which leads to the same questions being asked over and over and teams getting understandably frustrated.
A central knowledge base is the fix. It’s the single source of truth that helps both your internal teams and your customers find what they need, right when they need it. This guide will walk you through what an Atlassian knowledge base is, how to get it set up properly, and, most importantly, how to push past its limits to offer the kind of instant, automated support everyone expects these days.
What is an Atlassian knowledge base?
First things first, an "Atlassian knowledge base" isn’t a single product you can just go out and buy. It’s something you build by combining a couple of Atlassian’s main tools, primarily Confluence. Think of it as the central library for all your company’s how-to guides, policies, and internal wikis.
The role of Confluence and Jira Service Management in your Atlassian knowledge base
To make this work, you need two key players: Confluence and Jira Service Management.
-
Confluence: This is where you write, organize, and manage all your knowledge base articles. It’s your digital library, packed with features for collaborative editing, useful templates, and a page structure that helps keep everything from turning into a mess. Your team can jump in to write articles, track changes, and make sure all the information is accurate.
-
Jira Service Management (JSM): This is your help desk, the front door where employees or customers show up with questions. When you connect a Confluence space to a JSM project, it gets a whole lot smarter. As someone types their question into the help portal, JSM automatically looks through your knowledge base and suggests relevant articles. It’s a simple way to answer questions before a support ticket is even created.
Internal vs. external Atlassian knowledge bases
You can build an Atlassian knowledge base for two different audiences, and it’s good to know the distinction:
-
Internal Knowledge Base: This one is just for your team. Think of it as the home for employee onboarding guides, HR policies, IT troubleshooting steps, and documentation on internal processes. The goal is to make your employees more efficient and able to find answers on their own.
-
External Knowledge Base: This is for your customers. It’s your public help center, full of product guides, FAQs, setup instructions, and tutorials designed to help customers solve their own problems without needing to talk to anyone.
The setup process is basically the same for both, but you’ll want to be mindful of permissions and make sure you’re writing with the right tone for each group.
How to set up your Atlassian knowledge base: a step-by-step guide
Getting started is refreshingly simple. Atlassian gives you everything you need to build a well-organized and searchable library of information. Here’s a quick walkthrough to get your first knowledge base space up and running.
Step 1: Create your Atlassian knowledge base space in Confluence
Everything begins in Confluence. When you’re ready to build your library, you’ll need to create a new "space." Confluence helps you out here by offering a dedicated "Knowledge Base" template right from the start.
When you choose this template, you’ll be asked to name your space (something obvious like "Customer Help Center" or "IT Support Docs" is perfect) and set the permissions. You can make it public for anyone to see or lock it down for specific users. From there, you can add a logo and tweak the look to fit your company’s branding. This whole setup takes just a few minutes and gives you a great starting point.
Step 2: Structure your Atlassian knowledge base content with parent pages and labels
A disorganized knowledge base is almost as useless as having no knowledge base at all. Before you start writing articles, take a moment to think about the structure. A logical layout makes it much easier for people to browse and find what they’re looking for.
Pro Tip: A great way to organize is by creating a "parent" page for each major topic or product. Then, you can nest "child" pages underneath for specific guides and how-to articles. For example, you might have a parent page for "Billing" with child pages like "How to Update Your Credit Card" and "Understanding Your Invoice."
You should also make a habit of using labels. Labels are like tags that help you group content together across different sections. You can add labels like onboarding, billing, or troubleshooting to your articles to make them even easier to find via search.
Step 3: Write articles for your Atlassian knowledge base using templates
Consistency is a big deal if you want your knowledge base to look professional. The easiest way to nail this is by using templates. Confluence comes with a few pre-built templates for common articles, like a "How-to article" and a "Troubleshooting article."
Using templates makes sure every article follows a similar format, which helps users read and digest the information more easily. It also speeds things up for your team, since they can stop fussing with formatting and just focus on writing helpful content.
Step 4: Link your Atlassian knowledge base space to Jira Service Management
Once you have a Confluence space with a few articles in it, the last step is connecting it to Jira Service Management. Just pop over to your JSM project settings, find the "Knowledge base" section, and link your new Confluence space. This is the step that turns on the smart search and ticket deflection features in your customer portal.
Key features and limitations of an Atlassian knowledge base
An Atlassian knowledge base gives you a solid foundation for self-service support. But like any tool, it has its high points and its pain points. Knowing both is key to getting the most out of it.
What works well: core strengths of an Atlassian knowledge base
Atlassian really has the basics down, and there’s a lot to like about its native knowledge base setup.
-
The search is surprisingly smart: This is the main attraction. When a user starts typing in the JSM portal, the system instantly scans the linked Confluence space and pulls up relevant articles. It’s a fantastic way to head off common questions and lighten the load on your support team.
-
Version history and easy collaboration: Content goes out of date, it’s a fact of life. Confluence tracks every single change to a page, so you can easily see who changed what and when, and even roll back to an older version if you need to. That, plus its collaborative editor, makes it simple for teams to work together to keep information fresh.
-
You control who sees what: You have complete control over permissions. You can set them for an entire space (e.g., this whole section is for internal staff only) or get as specific as locking a single page to a certain group of users. This is perfect for managing both internal and external knowledge from one place.
-
Templates and macros save time: The built-in templates are a huge help, and Confluence macros let you build more dynamic content. For instance, the "Content by Label" macro can automatically create a list of all pages with a specific label, which is great for building dynamic index pages.
This tutorial provides a comprehensive overview of setting up and using a knowledge base in Jira Service Management.
Where you’ll hit a ceiling: common Atlassian knowledge base limitations
While the core functionality is solid, you’ll likely run into some walls as you start to grow if you’re only relying on the native Atlassian setup.
-
Someone still has to do the grunt work: JSM can suggest articles, but that’s where the automation ends. An agent still has to read a ticket, search for the right article if it wasn’t suggested, copy the link, and paste it into a reply. Customers also have to put in the work, scrolling through a document to find the one sentence that answers their question.
-
Your knowledge is stuck in Atlassian: Let’s be real, your company’s knowledge doesn’t just live in Confluence. It’s in Google Docs, Notion, Slack threads, and, critically, in thousands of past support conversations. A native Atlassian KB is completely blind to all of that, meaning its answers are only as good as the content you’ve painstakingly created in Confluence.
-
The content is static and reactive: Your knowledge base only knows what you’ve explicitly told it. It can’t learn from successful support tickets or figure out where the gaps in your documentation are on its own. This means keeping it up-to-date is a constant, manual chore that, more often than not, gets pushed to the back burner.
-
It can’t look up real-time data: A standard Confluence article is just text on a page. It can tell a customer how to check their order status, but it can’t actually check it for them. It can’t pull an account detail from your database or see if an item is in stock in Shopify. It’s a library, not a personal assistant.
How to supercharge your Atlassian knowledge base with AI
The fix for these limitations isn’t to ditch your Atlassian setup. You’ve already built a great foundation. The answer is to add a smart AI layer on top that can do the heavy lifting. This is exactly what tools like eesel AI are designed for, plugging directly into your existing stack to provide truly automated support.
Unify all your knowledge for your Atlassian knowledge base, not just your wiki
Instead of being stuck with only Confluence, eesel AI connects to over 100 sources right out of the box. You can connect it to your Confluence space, of course, but you can also hook it up to Google Docs, Notion, past help desk tickets, and much more.
This creates a single, unified brain for your support AI. It can pull information from every corner of your company, not just the official KB. This leads to more accurate, complete answers and less time spent manually copying information from one system to another.
Go from manual search to automated resolution in your Atlassian knowledge base
Instead of just suggesting links to articles, eesel AI’s agent reads the customer’s question, understands the context by searching across all your connected knowledge, and gives a direct, conversational answer right in the chat.
It can fully resolve tickets on its own, add the right tags, close the ticket, or hand it off to a human agent when it’s something truly complex. This moves you away from simple "ticket deflection" and into true "ticket automation," freeing up your team to focus on the tough stuff.
Pro Tip: With eesel AI’s simulation mode, you can test the AI on thousands of your past tickets and see what its resolution rate would be before it ever interacts with a customer. You can start small by automating simple topics and expand its responsibilities as you get more comfortable.
Close Atlassian knowledge base gaps automatically
One of the biggest headaches of managing a knowledge base is keeping it current. eesel AI helps solve this by analyzing your resolved tickets. When it notices an agent provides a great answer to a new question, it can automatically draft a new knowledge base article based on that interaction.
This turns your support team into a content-generating machine without any extra effort, helping you find and fill the gaps in your Atlassian knowledge base with proven, real-world answers.
| Feature | Atlassian Knowledge Base (Alone) | Atlassian KB + eesel AI |
|---|---|---|
| Knowledge Sources | Limited to Confluence/Atlassian suite | Confluence, GDocs, Notion, past tickets, etc. |
| Support Workflow | Manual search & article suggestions | Fully automated answers & ticket resolution |
| Content Creation | Manual article writing | Automatic draft generation from tickets |
| Setup Time | Days to weeks to build content | Go live with an AI agent in minutes |
| Actions | Provides static information | Looks up live data & takes actions (e.g., triage) |
Build your Atlassian knowledge base foundation, then automate it
An Atlassian knowledge base is a fantastic starting point. Using Confluence and Jira Service Management together gives you a solid system for organizing information, deflecting common questions, and helping your agents find answers more quickly. It’s the right first step to take.
But in a world where people expect instant, 24/7 support, a manual knowledge base on its own just doesn’t cut it. It takes too much work to maintain and can’t tap into all the knowledge scattered across your company.
By adding an AI automation layer like eesel AI, you can turn your static library into a powerful support agent that’s always on. It learns from all your data, provides direct answers, and resolves issues automatically, finally unlocking the real value of the knowledge you already have.
Ready to see what your knowledge base is really capable of? Connect your Atlassian knowledge base to eesel AI in just a few minutes and find out how much you can automate.
Frequently asked questions
Start small by focusing on high-impact content. Ask your support team for the top 5-10 questions they answer most often and write simple how-to or troubleshooting articles for those issues first. This approach provides immediate value and helps you build momentum.
While you technically can, it’s usually better to create separate Confluence spaces for each audience. This allows you to tailor the tone and technical depth of the content appropriately and use permissions to ensure sensitive internal information is never exposed to customers.
The key is to establish a clear ownership and review process. Assign owners to different content categories and set a regular cadence (e.g., quarterly) for them to review and update articles. Tools like eesel AI can also help by automatically identifying knowledge gaps based on new support tickets.
Yes, typically you need active subscriptions for both Confluence and Jira Service Management. They are distinct products that integrate tightly to provide the knowledge base functionality, with Confluence acting as the content repository and JSM as the help portal.
Native search only suggests links to articles, meaning agents and customers still have to do the manual work of finding the specific answer. An AI layer provides direct, conversational answers, can fully resolve tickets on its own, and learns from all your company knowledge, not just what’s in Confluence.
