Atlassian Intelligence

Overview

Atlassian Intelligence leverages a combination of OpenAI''s technology and Atlassian''s own AI models to embed generative AI capabilities across its suite of cloud platform products, including Jira Software, Confluence, Jira Service Management, Trello, and Bitbucket. The primary goal is to accelerate teamwork, improve decision-making processes, and streamline various workflows by deeply understanding the context of a user''s work within the Atlassian ecosystem.

Its unique strengths lie in its contextual assistance tailored to project management and software development lifecycles. Key features include AI-driven summarization of lengthy documents, complex issue threads, or comment histories; generation of draft content such as test plans, meeting summaries, or email responses; transformation of selected text to different tones or formats; and natural language querying of project data (e.g., ''summarize open issues for project Alpha'').

Atlassian Intelligence enhances productivity by reducing time spent on information gathering and routine content creation, allowing teams to focus on more strategic tasks. Its seamless integration within familiar Atlassian tools means users can leverage AI without context switching, fostering efficiency and enabling faster, more informed actions relevant to their ongoing projects and collaborative efforts.

Key Features

• AI-powered summaries of Jira issues, Confluence pages, and comment threads.
• Generative AI for drafting content (e.g., meeting notes, test plans, email responses).
• Natural language to Jira Query Language (JQL) translation for easier issue searching.
• Text transformation (e.g., change tone, summarize, find action items).
• AI-powered virtual agent capabilities in Jira Service Management for automated support.
• AI-assisted coding suggestions and explanations in Bitbucket (rolling out).
• Contextual understanding based on a team''s specific work and data within Atlassian tools.
• Lookup for internal acronyms and project-specific terminology.
• Debugging assistance for CI/CD failures in Bitbucket and Jira.

Supported Platforms

• Web Browser (via Atlassian cloud products)
• API Access (via Atlassian platform APIs for developers)

Integrations

• Jira Software
• Confluence
• Jira Service Management
• Trello
• Bitbucket
• Atlas (Atlassian product)
• Utilizes OpenAI models in conjunction with Atlassian''s own AI.

Use Cases

• Quickly understanding long Confluence pages or Jira issue comment histories through AI summaries.
• Drafting initial content for new documentation, project plans, or team updates within Confluence.
• Generating Jira Query Language (JQL) statements using natural language to efficiently find specific issues.
• Automating responses and creating knowledge base articles in Jira Service Management.
• Explaining complex code snippets or suggesting bug fixes within Bitbucket.

Target Audience

• Software Developers
• Project Managers
• Product Managers
• IT Support Teams
• Technical Writers
• Teams using Atlassian cloud products for collaboration and project management.

How Atlassian Intelligence Compares to Other AI Tools

Pricing Tiers

Roadmap & Upcoming Features

Initial announcements and beta rollouts began around April 2023, with broader availability and feature expansion throughout late 2023 and early 2024.

Continuously updated. Significant new capabilities and enhancements are rolled out frequently, with major announcements typically aligning with Atlassian events or quarterly updates (e.g., Q1-Q2 2024 updates included expanded CI/CD insights and improved search).

Upcoming Features:

• Continued expansion of AI capabilities across more Atlassian cloud products and use cases.
• Deeper integration with third-party tools and data sources via the Atlassian platform.
• More sophisticated AI-driven analytics, reporting, and insights for project management.
• Enhanced AI-powered assistance for software development, including more advanced code generation and review features.

User Reviews