Atlassian Rovo empowers organizations with the help of AI-powered agents

Atlassian recently unveiled Rovo, a new product designed to surface relevant and contextual results across several data sources and formats, which can be turned into actionable insights and knowledge-driven decisions. Atlassian Rovo was created to face the challenges faced by teams trying to find timely and relevant answers to their queries and keep up with the information trapped in an increasing number of applications used across organizations. According to a Gartner survey, 47% of digital workers struggle to locate the information they need to perform their jobs effectively.

To solve the problem of how teams find, learn, and act on information dispersed across internal tools, Rovo leverages Atlassian's deep understanding of teamwork patterns, organizational structures, and lines of communication gained over Atlassian's past 20+ years of experience, and encapsulated in its proprietary "teamwork graph" data model. The teamwork graph data model extracts information from every source that users decide to connect to Rovo, ranging from popular SaaS apps to custom, homegrown workflows for departments such as HR or finance. Once the data sources are in place, Rovo empowers users to find, learn, and act from highly relevant and contextual replies to their queries.

In addition to integrating with Atlassian tools like Jira, Rovo can search for answers by integrating seamlessly with third-party content like files from Google Drive, SharePoint, and Slack. Rovo can also query custom enterprise data sources like proprietary HR or finance systems. Search respects permissions established by administrators, who can connect additional sources and establish data answers for individual users. Thus, employees will not accidentally access information they are not supposed to see in the first place.

The information uncovered by Rovo is then presented in a user-friendly format that supports interactive learning for a deeper understanding. Answers are organized in knowledge cards providing contextualized snapshots of specific information on projects, goals, teammates, and other topics of interest drawn from customers' enterprise data. Knowledge cards improve over time as more information is added to the teamwork graph. Answers can also be accessed via Rovo Chat, the software's conversational chatbot, improving over time as more data is connected. Finally, Rovo also suggests other relevant topics and follow-up questions enabling a deeper understanding of the original query.

Finally, Rovo assists users in taking action by providing AI-powered agents with special skills and knowledge fit for workflows and processes in varied areas within an organization. Agents can:

• Generate, review, and refine content for marketing and PR communications;
• Automate and streamline tasks such as creating a design for new requests; and even
• Help with new employee onboarding, building team gratitude, and facilitating team collaboration.

Since they are built for an enterprise setting, administrators can fully control agents, and agents will report back to them, regardless of whether they are working alongside humans. They can also be configured to spring into action after a specific trigger. Agents can be easily created by following one of the 20 templates, using Atlassian’s no-code text interface or Forge, or obtained on the Atlassian Marketplace. Atlassian Rovo has already been deployed by a selection of the company's customers, and interested organizations can join Atlassian's waitlist to try out Atlassian Rovo as soon as it is available.