Rovo Search can also learn and explain unfamiliar jargon specific to an industry or individual business based on the organization’s documents. This enables Rovo to provide definitions for acronyms and terms that appear within a Confluence document, for exam-le. It’s proved to be a popular feature, Atlassian said, and is used by three-quarters of staff testing Rovo.
A semantic search function helps teams “connect with what they are looking for,” said Julie Mohr, principal analyst at Forrester, as well as “knowledge they didn’t know existed.” This helps employees “work the way they want to work with a comprehensive set of expressive tools — from video to pages, structured and unstructured, it is all knowledge,” she said.
Another way to search for information is via Rovo Chat. Similar to the conversational interfaces in Microsoft’s Copilot, OpenAI’s ChatGPT, and others, the chatbot responds to user questions in natural language, with answers based on data held in documents across an organization. Links are provided to the original source.
Atlassian Rovo Chat uses genAI and a chatbot interface with natural language processing to deliver information to users.
Atlassian
Another aspect of Rovo that relies on generative AI is the addition of workflow automation “agents.” Accessible via the Rovo Chat sidebar, the Rovo Agents are tailored to a specific task. For instance, Rovo Agents can be designed to generate and review marketing content, collate feedback from various sources, or streamline processes such as clearing up Jira backlogs and organizing Confluence pages.
Users can create their own Rovo Agents using a no-code text interface or Atlassian’s Forge app development platform. Atlassian expects there will be around 20 pre-built agents available when Rovo launches.
Canva’s design software is an example of an Atlassian partner building its own agent. “There’s going to be a Canva agent that helps with generating simple artwork for social media posts, things that you don’t need an expert designer to do,” said Valliani.
