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Integrate Artificial Intelligence (AI) to Jira Data Center

Atlassian Intelligence, a suite of AI-powered features designed to enhance productivity and streamline workflows has been introduced in 2023. However, Atlassian Intelligence is only available for Cloud products,the Data Center products have not yet incorporated this functionality. We will introduce how to implement Intelligence features in Jira Data Center.

AI for Jira is just the one to bring intelligence features to Jira Data Center.

Prerequisite of Using AI for Jira

Using AI for Jira requires the presence of a Large Language Model (LLM), AI for Jira supports multi LLMs including:

  • Commerical Large Language Model:
    • OpenAI ChatGPT
    • Azure openAI
    • QWen
  • Open source LLM deployed on primise
    • Models based on the Ollama framework: Llama, Gemma, Mistra, Phi, …

It’s required for Jira administer to configure AI Provider in the app settings first.

AI-for-Jira-Configuration.png

How AI for Jira works

The basic work flow of AI for Jira is as follows:

AI-for-Jira-Workflow.png

  1. User queries in Jira (for JQL in search bar or content generation in editor )

  2. Prompt handler change the query string to appropriate prompts that can be understood by LLM, and send the prompts to LLM Gateway

  3. LLM Gateway will call LLM based on the configuration of which model is used.

  4. When the response is generated, the Response Handler retrieve valuable message and adapt proper format to user.

Highlight Features of AI for Jira

Natural Language <--> JQL

Jira Query Language (JQL) is a robust tool that can be challenging to master. Even seasoned Jira users may have difficulty crafting accurate queries that meet their business needs due to unfamiliarity with JQL syntax. This is where AI for Jira comes in, simplifying the process by allowing you to express your requirements in natural language. The app will then automatically generate and execute the appropriate JQL queries, saving you time and effort.

JQL-search-1.png

On the other hand, If you're working with complex JQL queries, AI for Jira can provide you with clear explanations of their nuances. This can be particularly helpful in ensuring that you fully understand the query and can make any necessary adjustments for optimal results. With AI assistance, you can streamline your JQL queries and improve your overall productivity.

JQL-Explain.png

Content Generation in Jira Editor

Creating content in Jira, such as drafting requirements or test cases, can be a time-consuming and challenging task. However, with the help of AI-generated content, we can improve our writing and make the process more efficient. At present, Jira's Issue descriptions and comments can employ AI writing.

AI-generated content includes the following features:

  • Summarize writing

  • improve writing

  • Fix spelling & grammer

  • Brainstorm

  • Make shorter

  • Change tones to:

    • professional

    • empathetic

    • casual

    • neutral

    • educational

Content-Generation-Jira-Editor.png

 

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Zhaocheng Zhou September 5, 2024

Promote new dynamics of team collaboration

The integration of AI in Atlassian Jira Data Center not only increases individual productivity, but also pushes team collaboration to a higher level. AI for Jira allows teams to collaborate more smoothly through intelligent queries, content generation, and language understanding, ensuring that everyone gets the right information at the right time.

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