What are the AI prospects with Atlassian ROVO?

Introduction

This post is an introduction to Atlassian's AI response, outlining the technical fundamentals and some simple use cases per app.

Atlassian's AI solution is called ROVO; it is based on fundamental LLM models and a proprietary Teamwork Graph that acts as a RAG.

This energetic shift towards generative AI explains Atlassian's equally proactive cloud strategy. In other words, Rovo's leverage is essentially available in the cloud.

Rovo also forms the basis of an agentic solution that complements automation rules. Users can use native agents or configure their own agents with Studio, or engage Rovo Forge developers for specific needs.

Governance is certainly not overlooked, with contextualized rights management and auditability of ROVO actions. And where there's data, there are connectors, which are also available.

The call to Rovo is usually made by clicking the "Ask Rovo" button, regardless of the application you are using. A panel similar to that of ChatGPT then opens.

In summary, a very similar approach to what is found with other software publishers, notably Microsoft with Copilot and Copilot Studio.

Jira

What are the benefits for Jira users? based on the response to a prompt formulated in a ROVO window.

• Obtaining a semantic summary on tickets

• Create or update tickets based on criteria expressed in natural language

• To be the decision-making source for a transition in a workflow

• Create a Confluence page based on Jira ticket analysis

All of this is particularly interesting because the quality of the result will depend on the prompt or instructions of the agent, and on the knowledge base targeted via Teamwork Graph.

Thus, those who have business tickets (for example quality) will be able to rely on Rovo to automate time-consuming tasks, while maintaining control.

Rovo offers, the user has .

Confluence

What are the benefits for Confluence users? based on the response to a prompt formulated in a ROVO window.

The basic goal is to retrieve the result of a ROVO prompt into a Confluence page.

• I request a natural language summary of the status of Jira tickets for an Atlassian project and consolidate everything into a Confluence page by clicking "Insert into page".

• I request a summary of a topic (AI Compliance) using web search and deep search options, and store it on a Confluence page.

• I ask Rovo to generate a Confluence page (SOP, Instructions, etc.) from the fundamental models, the web, or my knowledge base itself under Confluence.

The applications are numerous and will depend on your prompts, agents, and knowledge bases. Change management is essential here, as the subject can be daunting for a number of legitimate reasons.

Jira Service Management

What are the benefits for users of Jira Service Management ?

ROVO takes on its full value here by becoming the engine of virtual agents that can thus suggest simple answers, or even solve them automatically via rules that use Atlassian's AI: Rovo.

Incident investigation is facilitated if the knowledge base is populated.

The same applies to impact analysis and risk management.

In general, the use of virtual service agents based on a Confluence knowledge base and automated rules based on ROVO opens up a range of possibilities.

Conclusion

Provided that special attention is paid to data in the Atlassian environment, user training in ROVO is a source of both quality and efficiency.

Of course, for regulated processes, a compliance dimension must be implemented. We support you in its assessment and implementation.

Atlassian apps (Jira, Confluence, Jira Service Management, and Bitbucket) enable the digitization of processes. The Atlassian platform facilitates data governance and allows Atlassian's AI (Rovo) to access numerous use cases at a very reasonable cost and within a very reasonable timeframe.

To be continued...

Feel free to contact us to move forward: contact@adn.fr