A quick start guide to Rovo Agents

After formalizing the launch of Rovo during Atlassian Team 24 Europe, there has been a growing interest in the uses this new artificial intelligence companion offers to current users of Atlassian Products and beyond. This blog post will explore the increasing list of uses Atlassian Rovo can do, focusing on the Rovo Agents, which promise to upgrade use cases in very specific situations.

As Rovo is not the same as Atlassian Intelligence, given the first one is a standalone product that works beyond Atlassian products, and Atlassian Intelligence enhances core product functionality. At the same time, Rovo amplifies productivity by extending capabilities across diverse tools and sites, boosting organizational efficiency, and bringing the best out of your current information within your systems.

Among the benefits customers are already reporting by using Rovo, they have stated that Rovo’s AI-driven capabilities make it a strong fit for enterprise teams. Whether they’re managing distributed teams or very complex projects, AI-powered automation saves time, improves cross-team communication, and enhances the flow of everyday tasks. It enables team members to prioritize meaningful tasks and make them focus on decision-making.

The use you give to the product will depend on your needs and your role. Rovo can help engineers save time by reducing issue analysis and minimizing context switching, or it can help team leaders quickly access multi-level information about complex projects.

To better understand this product, Rovo has been built considering, first, The Teamwork Graph, a framework rooted in two decades of studying organizational team collaboration, connecting all parts, and enriching Atlassian products. Rovo uses this foundation to streamline workflows and support seamless teamwork to build its main features, which revolve around three main pillars: Find, Learn, and Act

Find: Referring to the ease of access to relevant data from different tools, platforms, and third-party or custom websites, getting accurate contextual results.
Learn: Based on the data found, AI-powered insights features such as knowledge cards and chats will enable a new way to understand your company's data.
Act: Based on the use of specialized agents, it helps to manage routine tasks, simplify complex content, and save tons of time by enhancing productivity.

Those pillars work as an introduction to the continuously evolving features introduced by now:

Rovo Search: This feature allows you to find comprehensive results and centralize them from external sources and Atlassian products in one place.
Knowledge Cards: These are snapshot views that summarize and are backed by company data and insights to speed up decision-making.
Topics: This feature automatically shows definitions and related resources by underlining key project terms and acronyms.
Rovo Chat: The good old chat, this time with Rovo, enables collaboration and guidance using your system information and AI capabilities.
Rovo Agents: As one of the most essential features of this product, agents are extensions that automate tasks based on the area of specialization of that agent. There are three different types of these agents, which we’ll explain further in the following.

Learn in detail about Atlassian Rovo features >>

What are Rovo Agents?

Rovo Agents are customizable AI assistants that can be activated or created by any team member. They can be used in the Rovo Chat, automation rules, Confluence, and Jira by typing "/ai."

Rovo Agents are mainly designed to complement your work to achieve established goals, reduce repetitive tasks, and take actions based on a specialization area, they draw data from different knowledge sources from both Atlassian products and connected third-party tools.

There are three different types of Rovo Agents:

Out-of-the-box Rovo Agents. These are the ones Atlassian has included by default within the Agent's "market," depending on your choice, those might help with writing release notes, translating content into multiple languages, grooming your backlog, and more. As you can see below:
Custom Rovo Agents. There's a possibility to build your own Rovo Agent, and that can be done based on no-code/low-code builts or following the standards of the Forge platform. Learn how to create them.
Atlassian Marketplace Rovo Agents. Some solutions already available in the marketplace have developed AI capabilities, such as Budgety, which helps you get specific information using the Rovo machinery to get the information you need at the moment you need it. Each of these solutions works data based on a specific area of solution.

As you can see in the following, Budgety for Jira, a budget management solution available in the Atlassian Marketplace, can return in which areas this budget is the money being spent (i.e., marketing, production, design, research, etc.), the amount spent, and the total for each with a correspondent description, you would need to use the prompt "Categorize [name the budget] budget costs":

Budgety for Jira as a Rovo Agent

As mentioned, Budgety it’s a solution for budget management and cost tracking for Jira available in the Atlassian Marketplace. This solution allows cost-tracking capabilities to monitor expenses, categorizing them as direct or indirect, Capital Expenditures (CAPEX), or Operational Expenditures (OPEX). Besides, it offers real-time reporting, providing actionable insights about budget performance and enabling data-driven decision-making.

As a Rovo agent, Budgety offers advanced forecasting capabilities, predicts future budget trends, identifies potential risks, optimizes resource allocation, and maximizes budget impact. This comprehensive AI-powered approach to budget management will improve cost visibility, enhance decision-making, and ultimately achieve greater budget efficiency. Learn more about it in this demo: