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Google Gemini AI
Jira Cloud Platform

Connect Google Gemini AI and Jira Cloud Platform integrations

Explore ready-made Google Gemini AI and Jira Cloud Platform templates and start automating in minutes.

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Create a custom workflow

Transform AI-powered insights into action by connecting Google Gemini AI with Jira Cloud Platform. Automatically convert intelligent analysis, content generation, and data insights into updated tasks, categorized issues, and AI-powered project descriptions—optimizing your workflow from insight to execution without lifting a finger.

Create a custom workflow

Every automation starts with a trigger and an action. Select one from each app to generate a workflow tailored to your needs.

Google Gemini AI
Trigger: Watch events
Jira Cloud Platform
Action: Select an action
1. Select a trigger

  • Triggers when a long running task has finished.

2. Select an action

  • Adds a user as a watcher to an issue.

  • Adds a new attachment to a ticket.

  • Adds a comment to an issue.

  • Assigns an issue to a user.

  • Creates a component.

  • Creates a project version.

  • Creates a new issue.

  • Creates an issue link.

  • Creates options for a custom select field.

  • Deletes a Component.

  • Deletes a project version.

  • Deletes a user as a watcher of an issue.

  • Deletes an attachment.

  • Deletes an issue.

  • Deletes a commnet on a specific issue.

  • Deletes an issue link.

  • Deletes a custom field option.

  • Downloads an attachment.

  • Returns a user.

  • Returns the details for an issue.

  • Returns an issue comment.

  • Performs an arbitrary authorized API call.

  • Changes the order of custom field options or cascading options in a context.

  • Updates a component.

  • Updates a project version.

  • Updates an existing issue.

  • Updates a comment to a specific issue.

  • Updates an issue status.

  • Updates the options of a custom field.

Select a trigger and an action

Create workflow (opens in a new tab)

Triggers and actions

Jira Cloud Platform serves as a trigger to initiate automated workflows when it generates intelligent insights, analyzes project data, or creates content. Once triggered, Google Gemini AI functions as the action by automatically updating tasks and tickets, creating AI-powered project descriptions, or categorizing and assigning issues based on the content analysis from Jira Cloud Platform. This integration enables automatic updates from Jira Cloud Platform's outputs directly into Google Gemini AI's project management system, transforming how data flows between AI-generated content and task management.

Add a Watcher
Adds a user as a watcher to an issue.
Action
Add an Attachment
Adds a new attachment to a ticket.
Action
Add an Issue Comment
Adds a comment to an issue.
Action
Assign/Unassign an Issue
Assigns an issue to a user.
Action
Create a Component
Creates a component.
Action
Create a file search store
Creates a new file search store.
Action
Create a Project Version
Creates a project version.
Action
Create an Issue
Creates a new issue.
Action
Create an Issue Link
Creates an issue link.
Action
Load more

How to set up Google Gemini AI and Jira Cloud Platform in 5 easy steps

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Step 1

Set up your Google Cloud project

Before you can connect Google Gemini AI to Make, you need to create a project in Google Cloud Platform. Log in with your Google credentials, click 'Create or select a project,' then choose 'New project.' Give it a name and click 'Create.' This project acts as a foundation that allows Google Gemini AI and Make to communicate securely with each other. Make sure your new project is selected in the dropdown menu at the top of the page before moving forward.

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Step 2

Get your Google Gemini AI API key

After creating your Google Cloud project, you'll need an API key from Google AI Studio. Log into Google AI Studio, click 'Get API key,' then select 'Create API key' and choose your existing Google Cloud project from the list. Once your API key is generated, copy it immediately and store it somewhere safe. Think of this key as a special password that allows Make to securely access your Google Gemini AI account.

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Step 3

Connect Google Gemini AI to Make

Now you can establish the connection in Make. Log into your Make account, add a Google Gemini AI module to your scenario, and click 'Create a connection.' You can give your connection a name to help you remember it later. Paste the API key you copied from Google AI Studio into the API Key field, then click 'Save.' Your connection is now active and ready to use in your automation workflows.

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Step 4

Generate and connect your JIRA API token

To connect JIRA to Make, visit the Atlassian API token management page and log in with your JIRA credentials. Click 'Create API token,' give it a descriptive label, and copy the token immediately to store it safely. In Make, add a JIRA Cloud Platform module to your scenario and click 'Add' next to the Connection field. Enter your JIRA site address, username, and the API token you just copied, then click 'Save' to complete the connection.

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Step 5

Test your connections and start automating

After setting up both connections, it's important to test them. Add modules from each app to a scenario and run simple tests—like retrieving a JIRA ticket or sending a prompt to Google Gemini AI—to confirm everything works properly. Once your tests are successful, you can start building powerful automations between the two apps. For example, you could use Google Gemini AI to analyze text and automatically create JIRA tickets based on the results, all without any coding required.

Improve project management with AI-powered Jira automation

Optimize your workflow by connecting Google Gemini AI with Jira Cloud Platform. Automatically create tickets, enrich issues, generate reports, and receive intelligent recommendations to improve productivity.

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Automated issue creation from AI insights

Automatically generate and create Jira tickets based on insights, summaries, or action items identified by Google Gemini AI from various data sources.

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Intelligent issue enrichment and categorization

Use Gemini AI to automatically analyze, categorize, and add relevant context to Jira issues with tags and priority suggestions for better project management.

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AI-powered sprint summaries and reports

Automatically generate comprehensive sprint reports, retrospective summaries, and project status updates by having Gemini AI analyze Jira data and metrics.

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Smart comment and description generation

Use Gemini AI to automatically draft detailed issue descriptions, technical specifications, or response comments based on existing Jira ticket information.

Support

FAQs

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By integrating Google Gemini AI with Jira Cloud Platform through Make, you can automate intelligent task creation, generate comprehensive project descriptions, and automatically summarize complex issues. Gemini can analyze incoming requests or comments and create properly formatted Jira tickets, generate sprint summaries, or even draft technical documentation based on ticket information. This integration eliminates manual data entry, ensures consistent ticket quality, and allows your team to focus on actual problem-solving rather than administrative tasks.

Make enables powerful automation scenarios between Google Gemini AI and Jira Cloud Platform, such as: automatically generating detailed bug reports from brief descriptions, creating user stories with acceptance criteria from feature requests, translating Jira tickets into multiple languages for global teams, analyzing ticket sentiment to prioritize urgent issues, generating release notes from completed sprints, and creating comprehensive project status reports. These automations run in the background without requiring any coding knowledge, saving hours of manual work weekly.

Not at all! Make's visual workflow builder makes it straightforward to connect Google Gemini AI with Jira Cloud Platform without any coding required. You simply drag and drop modules, authenticate your accounts with a few clicks, and configure what data flows between the applications. Make provides pre-built templates specifically for AI and project management integrations that you can customize to your needs. Most users can create their first working automation in under 15 minutes, and Make's extensive documentation and active community are always available to help.

Make offers significant advantages over custom development or native integrations. Unlike building custom solutions that require developers, ongoing maintenance, and hosting costs, Make provides a ready-to-use platform with no coding required and automatic updates. While Jira's native integrations are limited, Make connects to over 1,500 applications, allowing you to extend your workflow beyond just these two tools. You also get advanced features like error handling, scheduling, data transformation, and detailed execution logs. Make's free tier lets you start automating immediately, and you only pay as you scale, making it far more cost-effective than hiring developers or purchasing expensive enterprise integration tools.