Can ChatGPT access Confluence? A 2026 guide

Your team's brain lives in Confluence. It’s a mature, reliable platform where every project plan, technical doc, and meeting note is carefully stored. Then there’s ChatGPT, which has completely changed how we find information. So, the question on everyone’s mind is: can you get these two to talk to each other? Can ChatGPT access Confluence and pull out instant, smart answers from your company’s own knowledge?

The short answer is yes, though it involves choosing the right integration method for your needs. Many teams explore this to streamline their workflows, a topic often discussed in threads on

and the Atlassian community.

This guide will walk you through the different ways to connect ChatGPT to Confluence, from simple copy-paste methods to more specialized integration platforms. We’ll look at the strengths of each approach and show you the most straightforward way to turn your Confluence wiki into a genuinely useful AI assistant.

Understanding Confluence and ChatGPT

Before we get into the how-to, let's do a quick refresher on these two tools and why getting them to work together is such a big deal for so many businesses.

What is Confluence?

Confluence is the industry-leading central place where your team creates, organizes, and talks about work. It serves as your official source of truth, using Pages and Spaces to hold everything from project specs and meeting notes to company policies and how-to guides. It is a powerful foundation for your company's knowledge.

What is ChatGPT?

ChatGPT is a large language model from OpenAI that’s excellent at understanding and writing like a human. You can ask it to explain a tricky concept, summarize a long document, or answer pretty much any question you throw at it. Its conversational style has made it a go-to tool for getting information fast.

Why connect ChatGPT and Confluence?

When you bridge the gap between these two, you get some great perks that modern teams are looking to leverage:

• Stop digging for answers. You can get immediate responses to your questions without having to manually search through your extensive library of Confluence pages.

• Give your team their time back. Less time spent searching for information means more time to focus on the high-impact work that matters.

• Get summaries on demand. Instantly boil down long project documents, technical guides, or meeting notes into the key points you actually need.

• Put support on autopilot. You can power internal support bots for HR or IT questions, or even help out your customers with a chatbot that uses your trusted documentation as its brain.

How to connect ChatGPT to your Confluence data

It’s obvious that connecting these two is a significant win, but how you do it makes all the difference. Let's break down the common methods, from the simplest to the most effective.

Method 1: The manual 'export and pray' approach

The most basic method is to export a Confluence space as a PDF or Word document and then upload that file to a custom GPT. This is often the first step teams take to see how AI handles their data.

The considerations:

• Data updates. The AI's knowledge is based on the data at the time of export. When your team updates a page in Confluence, you would need to re-export and re-upload the files to keep the GPT's knowledge current.

• Formatting changes. Confluence pages are rich with tables, macros, and specific layouts. When you export to a PDF or Word doc, some of that complex structure might look different to the AI, which can occasionally affect how answers are formatted.

• Granular control. This method is a bulk approach. It can be more challenging to pick and choose specific pages to sync or manage detailed access permissions for the AI.

Method 2: The technical DIY route with custom GPT Actions

If you have developers on hand, building a custom GPT Action is another option. This involves creating a direct, real-time API connection to Confluence. As noted in guides like the OpenAI Cookbook, this process involves creating an app in the Atlassian developer portal and configuring OAuth 2.0 authentication.

The considerations:

• Technical complexity. This method requires developer resources and a solid understanding of API integrations and authentication. It is often treated as a specialized engineering project.

• Ongoing maintenance. APIs and security protocols evolve over time. Any updates on the Confluence or OpenAI side might require engineering attention to ensure the custom-built connection remains seamless.

• Security management. As discussed in the Atlassian Community, managing secure access is an important consideration. When building a custom solution, your team handles the governance and security configurations.

Method 3: Using third-party integration platforms

Third-party tools can offer a balanced approach, simplifying the connection while utilizing Confluence's robust API.

Automation platforms like Zapier

Tools like Zapier operate on a trigger-and-action model. For instance, you could set up a Zap where "When a new page is made in Confluence, summarize it with ChatGPT." These are excellent for specific, linear tasks.

Marketplace apps

There are many great apps on the Atlassian Marketplace that add AI features directly inside the Confluence interface, such as summarizing pages or helping with content creation. These tools are perfect for users who primarily work within the Confluence platform.

Dedicated AI integration platforms

This brings us to platforms designed specifically to create and deploy AI assistants using your existing company knowledge.

This is what eesel AI does. It provides a no-code platform that works alongside Confluence and your other apps to build an AI assistant.

Here’s why this approach is beneficial:

• Quick deployment. It offers a one-click integration, allowing you to have a working AI assistant ready for testing very quickly.

• Bring all your knowledge together. Confluence is often the hub, but you might have data in other places too. With eesel AI, you can pull in knowledge from Google Docs and over 100 other sources to create a unified brain for your AI.

• Use your AI anywhere. The assistant can be deployed in Slack for internal questions, in your helpdesk to help agents, or as a customer-facing chatbot on your website.

• Specific control. You decide exactly which Confluence Spaces and pages the AI learns from, ensuring it provides answers based on the most relevant information.

A comparison of the integration options

Let's look at how these methods compare in practice.

With a manual export, setup is fast, but you'll need to periodically update the files to keep the data current. It's a simple way to get started with a specific set of documents.

The DIY custom GPT approach provides real-time data but requires significant developer time to build and maintain. It's a powerful option for teams with dedicated engineering resources who want a bespoke connection.

Automation platforms are great for specific triggers and linear workflows. They have moderate maintenance needs and work well for automating individual tasks.

Finally, a dedicated platform like eesel AI offers a no-code setup that stays updated in real time. It allows you to unify knowledge from Confluence and many other sources and deploy that AI assistant across different channels.

What do Confluence integration solutions cost?

There are several pricing models to consider depending on your team's size and needs.

• Confluence AI (Rovo): Confluence offers tiered plans to match different team sizes. Its AI, Rovo, uses a credit system that allows for scalable AI usage. According to Atlassian's pricing page, Standard and Premium plans provide different credit tiers, giving teams the flexibility to choose the right level for their needs.

• DIY / Custom GPT: The primary cost here is developer time for initial construction and ongoing maintenance, plus the separate OpenAI API fees based on usage.

• Automation Platforms: Platforms like Zapier charge based on the number of automated tasks you run, with various plan levels available for growing teams.

• eesel AI: This platform offers transparent, predictable pricing with plans starting at $299/month ($239/month if billed annually). Plans are based on usage rather than per-ticket fees, allowing you to scale your AI assistant's reach with confidence.

The simplest way to let AI access your wiki

While there are many paths, a dedicated platform like eesel AI is designed to enhance your existing Confluence setup. It turns your Confluence docs into a reliable AI expert that you can put to work wherever your team needs it.

• Simple setup. You can connect your Confluence account with a single click. The platform is self-serve, making it easy to get up and running.

• Test with confidence. eesel AI includes a simulation mode that lets you test it on your past data. You can see exactly how it would have answered previous questions and fine-tune its behavior before it goes live.

• A versatile workflow engine. eesel AI is more than a chatbot; it’s a workflow engine. You can create custom actions, allowing it to triage support tickets, look up order details, or escalate issues to the right person.

What's the verdict?

Can ChatGPT access Confluence? Absolutely. Confluence is a mature, capable platform that offers the APIs necessary for these integrations to thrive. Whether you choose manual exports, a custom build, or a dedicated integration platform, you are unlocking the value of your team's collective knowledge.

For teams that need a reliable, scalable, and easy-to-manage way to tap into the knowledge stored in their Confluence wiki, a dedicated AI platform is a fantastic choice. it complements Confluence's strengths while giving you control over how that knowledge is used.

This video demonstrates how a custom bot using ChatGPT capabilities can interact with a knowledge base in Confluence to answer team questions.

Ready to connect your Confluence wiki to an AI that just works?

Get started with eesel AI for free and build your first AI assistant in under 5 minutes.