Atlassian Rovo: the next generation of AI-powered teamwork

At this year's Team '24 in Las Vegas, Atlassian had some major announcements, including the introduction of a new product: Atlassian Rovo.

Last year, Atlassian introduced its AI platform, "Atlassian Intelligence," aimed at helping teams increase productivity and efficiency. With Atlassian Rovo, Atlassian takes it a step further, using cross-tool AI to tackle the complex problem of enterprise search and knowledge discovery.

In this blog post, we explore what Atlassian Rovo is, how it works, and its potential to change the way companies manage knowledge and information.

What is Atlassian Rovo?

Atlassian Rovo is the result of the latest developments in AI technology, designed to help teams collaborate more effectively and make faster, more informed decisions. This new AI technology focuses on transforming information into action: it speeds up finding, learning, and acting based on information scattered across various internal tools.

Find

Rovo enables searches across various data, tools, and platforms, including third-party apps and in-house systems. This way, you get relevant results in your Atlassian environment without having to switch between different applications within a few seconds.

Learn

With Rovo, you gain a deeper understanding of your company's data. This is facilitated by AI-powered insights, knowledge cards, and an interactive AI chat function that supports deeper data exploration.

 

Act

Even the most capable teams can use a helping hand. Rovo agents understand complex tasks and take the right actions to help you achieve your goals. You can use specialized agents from the Atlassian Marketplace or create your own in a matter of seconds.

The Teamwork Graph: Atlassian's secret ingredient

The core of Atlassian Rovo is the "Teamwork Graph," a proprietary data model based on Atlassian's more than 20 years of experience. The Teamwork Graph pulls data from Atlassian tools and other SaaS apps to provide a comprehensive view of your company's goals, knowledge, teams, and work. The more data is connected, the smarter the graph becomes and the more relevant results Atlassian Rovo delivers.

How Atlassian Rovo improves enterprise search

Rovo revolutionizes enterprise search by not only providing relevant results but also allowing a deeper understanding of the data it finds:

• Contextual results: find exactly the information you need by searching across a wide variety of data sources, including Google Drive, Microsoft SharePoint, Slack, and GitHub.
• Personalized search: search results are tailored to your permissions and organizational profile, so you only see information that you're authorized to access.
• Industry-specific customization: Rovo comes with an API that allows industry-specific and custom applications to be connected, ensuring that even specialized data sources can be included.

Getting detailed answers from enterprise data

It may require multiple questions to gain a deep understanding of organizational issues. This is where Atlassian Rovo lends a hand:

• Instant, up-to-date insights through knowledge cards: knowledge cards provide contextual snapshots of specific information about projects, goals, new team members, and more, all based on your organization's enterprise data. Teams receive instant answers as they work, and the knowledge cards become smarter as more data is added to the Atlassian Teamwork Graph.
• A deeper understanding through Rovo Chat: Rovo Chat is an interactive conversational feature. Teams can ask questions, and Rovo provides comprehensive answers by combining data from various sources. This feature is powered by Atlassian Intelligence's advanced AI capabilities and becomes smarter over time the more it's used.

• AI-powered learning: as questions are answered, Rovo suggests related topics and follow-up questions that teams can use to explore further details. It also deciphers jargon by pulling information about unfamiliar acronyms and terms from Jira and Confluence.

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Automation with Rovo agents

Rovo agents are virtual team members specifically designed to operate in a variety of workflows. Not only can they automate tasks, but they can also help with complex decisions by analyzing data from different sources and making relevant suggestions.

Here are some examples of how Rovo agents can be used:

• Content creation: agents can help create, review, and refine content for marketing and PR, among other purposes.
• Automated tasks: agents can handle repetitive tasks like updating Jira issues or organizing Confluence pages.
• Knowledge management: agents can answer questions, integrate research into Jira specifications, create service checklists, or contribute to custom knowledge bases.
• Maintenance: agents can simplify time-consuming tasks like cleaning up Jira backlogs, structuring Confluence pages, or aligning content with formatting guidelines.
• Onboarding support: agents can assist in onboarding new employees by providing relevant information and encouraging teams to collaborate.