Rovo Chat just got smarter with new improvements powered by your Teamwork Graph

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Hi everyone! I’m Ashish, a product manager for Atlassian’s Teamwork Graph, and something I’ve been thinking about a lot is how to make chat tools really work for you. Without context, it’s really just a shot in the dark.

TL;DR: My team has been working to solve this problem by deeply integrating Teamwork Graph into Rovo to deliver answers that are not just smarter, but truly grounded in the context of your work. It's a big step toward giving you answers that actually make sense in the context of your work, not just generic AI replies.

We’ve always envisioned Rovo as your AI teammate, one that understands your team’s work and can surface the right information at the right time. Now, with these recent improvements, that vision takes a major step forward. Check out the full update in our recent blog.

This is the first of many improvements to the Chat function we have planned over the coming months and we will continue to update you with our progress along the way.

For now, let’s walk through what these changes mean for you.👇

1. Smarter answers with real-time context

Previously, Rovo Chat could only access indexed data from Teamwork Graph; which meant that for certain questions, Rovo lacked the full context needed for the best results. Now, Rovo Chat can directly query the full Teamwork Graph, tapping into the live web of 150+ relationship types that connect 45+ entities across Jira, Confluence, Atlas, Bitbucket, and Loom.

This means Rovo Chat can now deliver better answers to questions like:

• What goals are owned by xyz team

• Which PRs were authored by @XYZ last week

• Which confluence documents did I author last month..and more..

Before:
“What’s @Jordan working on?” → Returned everything Jordan had ever worked on, regardless of how recent or relevant.

Now:
Rovo Chat paints the full picture by pulling in things like linked PRs, tasks, and goals to show not just the “what” is Jordan working on but also the impact of that work to broader goals and objectives. This goes way beyond what you would find with a simple AI powered search and provides a better narrative for not just the work he’s doing, but the bigger picture of why it matters.

This means that users can get to the information they need faster and drive work forward with greater context. All of these relationships are live and deeply connected across Atlassian apps, so Rovo’s answers aren’t just smart, they’re grounded in your actual, current work.

2. Get time-bound summaries grounded in real-time work

Rovo has always summarized work, but now, those summaries are more powerful and precise than ever.

They’re now grounded in real-time activity across your Atlassian apps, not just a reference to an old doc or status page. That means when you ask for a summary, you’re getting the most current, context-rich view of what’s actually happening in your org.

Even better, summaries can now be grouped and filtered by project, person, or timeframe, so you can quickly tailor the insight to what matters most in the moment whether you’re prepping for a 1:1, reviewing a sprint, or catching up after time away.

Try asking:

• ‘What is keeping <teammate name> busy these days?’.

• ‘Give me a summary of all my work last week, grouped by projects’,

• ‘Can you tell me about all work done by <atlas team name> last week’,

• ‘Generate a summary of the work done by <person’s name>'s team last week’,

• Using deep research: ‘Generate a report of all work I’ve done in the last 6 months, organized by projects.’

Rovo brings you an instant, accurate, and flexible snapshot of recent work grounded in real updates you can trust to make decisions and take action.

3. Rovo now asks for clarification, so your intentions are never misunderstood

Rovo’s new clarification layer helps eliminate confusion in how your questions may be worded. If your query mentions a name or team that could refer to multiple entities, Rovo will proactively ask you to clarify before fetching the answer.

Say you type:

“What is Alex working on?”

If there are multiple users named Alex or several teams with “Alex” in them, Rovo presents options so you can pick the right one. In the example below, Rovo presents all relevant teams and prompts the user to specify which one they meant.

Rovo Chat’s deeper connection with Teamwork Graph brings more context, richness, and organizational data to your queries. In essence, it’s now “more correct” in its understanding of how your organization operates, and so your answers are also more correct. That means better summaries, faster answers, and fewer “let me clarify” moments.

Have a favorite query you will try? Found a way this can help your team work smarter? Drop it in the comments we’d love to hear from you.

Try the new experience in Rovo Chat today.