Atlassian has always been a leader in project management tools like Jira and Confluence, but the company is taking its innovation to a new level with Rovo AI. Introduced at Atlassian’s Team’24 Europe conference, Rovo AI is now generally available, offering a comprehensive AI platform that enhances productivity, improves workflow automation, and enables deeper insights through smart search capabilities and AI-powered agents.

In this article, we’ll dive deep into the features and benefits of Rovo AI, explore its AI-driven automation tools, and discover how Rovo will shape the future of work.

What is Rovo AI?

At its core, Rovo AI is an “AI teammate,” a smart assistant that integrates AI-powered tools across Atlassian’s suite of products, including Jira, Confluence, and other popular business tools. Rovo aims to help users automate workflows, improve efficiency, and handle mundane tasks, freeing up teams to focus on more important work.

Rovo consists of three core elements:

  1. Rovo Search - A comprehensive search engine that goes beyond Atlassian’s tools to provide information from third-party apps.
  2. Rovo Chat - A chatbot that allows users to interact with Rovo across different platforms and retrieve answers from the company’s internal knowledge base.
  3. Rovo Agents - AI agents that can automate repetitive tasks, reducing manual labor and increasing productivity.

By leveraging these core features, Atlassian customers can extend their subscriptions to include Rovo AI and unlock a whole new world of automation and intelligent assistance.

Rovo Search: A Comprehensive Search Engine

One of the most powerful features of Rovo AI is its search engine, which lets users search across all business-related data. Whether you need to access Confluence documents, Jira tickets, Slack messages, Google Docs, or even GitHub repositories, Rovo’s AI search engine has it covered.

With over 80 connectors planned in the next few months, Rovo Search can retrieve data from a wide variety of third-party SaaS tools, making it a comprehensive tool for business operations. For example, Figma files and Google Drive documents can easily be integrated into the search, allowing users to pull information from wherever it’s stored, making collaboration smoother than ever before.

Moreover, Rovo Search uses social signals based on Atlassian’s team graph to determine who you work with most closely. This means your search results will be ranked based on the team collaboration data, making them more relevant and contextual to your needs.

Rovo Chat: Bringing AI Conversations to Your Workspace

Rovo Chat adds another layer of AI-driven intelligence to the Atlassian ecosystem. Available within Atlassian’s tools, as well as through a browser extension, Rovo Chat allows users to initiate conversations with Rovo from anywhere. Whether you're working on a Google Docs file or reviewing Jira tickets, you can ask Rovo Chat questions about your organization's knowledge and receive contextual answers.

What makes Rovo Chat particularly powerful is its ability to analyze active web pages. For instance, if you’re working in Google Docs, you can ask Rovo Chat to retrieve relevant information from Confluence or Slack directly, enhancing your workflow efficiency without needing to leave the page.

Rovo Agents: Automating Workflows

Perhaps the most exciting part of Rovo AI is its AI agents, which automate many routine tasks that normally eat up valuable time. Instead of manually creating tasks or documents, you can instruct Rovo to handle these jobs through simple commands.

For example, if you create a document in Confluence with the hashtag #translate, Rovo can automatically trigger an AI agent to translate the document into different languages. With 500 pre-built AI agents already available and more on the way, the scope of automation is enormous.

Creating Your Own Agents

One of the most intriguing aspects of Rovo is its ability to allow users to create custom AI agents. These agents can be built using drag-and-drop features through a no-code AI agent builder, giving even non-technical users the ability to automate tasks. With plans to add 50 more data connections in the future, the customization of AI agents will become even more versatile, providing users with a greater level of automation and control over their workflows.

Rovo Agents vs. Workflows: What’s the Difference?

Many SaaS platforms are betting on automation with the goal of allowing AI agents to operate autonomously, without any human involvement. However, Atlassian has taken a different approach by focusing on keeping the “human in the loop.”

Unlike fully autonomous agents offered by other SaaS vendors, Rovo agents are designed to involve humans in the process. A user must trigger the agent, and they are also responsible for reviewing the results before proceeding. This ensures that the final outcome is always under human oversight, adding a layer of quality assurance that autonomous agents might lack.

While Rovo agents possess reasoning capabilities and can make decisions on their next actions, they often follow a structured path, giving them a balance between the workflow and AI agent paradigms. The future may see these agents evolve to become more autonomous, but for now, human oversight remains central to their functionality.

The Marketplace for Rovo Agents

As the popularity of Rovo AI grows, Atlassian has partnered with companies like Appfire, Usertesting, Onward, and Zapier to extend the capabilities of Rovo agents even further. The Atlassian Marketplace will soon feature more agents and agent capabilities, allowing customers to leverage a broad ecosystem of AI-driven tools to enhance their workflows.

By making Rovo agents available in the Atlassian Marketplace, businesses can integrate them into their existing workflows and customize their use according to specific business needs. The goal is to offer more tools for automating tasks like drafting release notes, generating bug reports, and creating OKRs, freeing employees to focus on higher-value tasks.

Atlassian Intelligence for Developers: Empowering Development Teams

Rovo AI isn’t just for project managers and business professionals—it’s also designed with developers in mind. As part of the Atlassian Intelligence platform, Rovo can assist developers with some of the most time-consuming tasks that don’t directly involve programming.

A new AI agent within Jira can now generate code plans, offer code recommendations, and create pull requests based on the description and requirements provided by the developer. This saves developers from having to wade through countless lines of code to figure out the next step in their project.

For instance, a developer working on a config issue or bug fix can rely on Rovo’s AutoDev agent to assist in resolving the problem. The agent analyzes data from Jira and Confluence and identifies issues that can be automated or fixed by the AI. While the AutoDev agent won’t act autonomously, it will present a solution and ask the developer for approval before taking action.

Pull Request Reviews and Code Improvements

In addition to the AutoDev agent, Rovo now offers a tool that accelerates the pull request review process. Regardless of which code management tool a team uses, Rovo analyzes the code and offers recommendations on how it can be improved, reducing the time developers spend on manual reviews and enhancing code quality.

This new AI-powered functionality helps streamline the entire development cycle, from writing code plans to submitting pull requests, ensuring that developers spend more time building features and less time on repetitive tasks.

Expanding Rovo AI’s Reach to Non-Atlassian Users

Despite the broad range of tools available within the Atlassian ecosystem, the company understands that not all employees use their products daily. To address this, Atlassian has made Rovo AI available to non-Atlassian users at no additional cost.

This ensures that businesses leveraging other SaaS tools can still take advantage of Rovo’s intelligent assistance, opening up possibilities for broader adoption and integration across various industries. Whether a company uses Slack, Figma, GitHub, or Google Drive, Rovo can seamlessly integrate and provide valuable insights through its search and automation capabilities.

The Future of Rovo AI: More Agents, More Automation

As Rovo AI continues to grow, Atlassian plans to release even more agents and expand the platform’s automation capabilities. The company’s vision is to continue enhancing Rovo’s intelligence while maintaining a balance between automation and human oversight.

While some companies aim for fully autonomous AI agents, Atlassian believes in keeping the human in the loop, ensuring that teams remain engaged in the decision-making process. However, as the platform evolves, there is potential for Rovo agents to become more autonomous, reducing the level of manual intervention required.

By staying committed to innovation and delivering AI-powered solutions that integrate seamlessly into existing workflows, Atlassian is positioning Rovo AI as a crucial tool for the future of work.