Connect Jira Cloud Platform and Google Gemini AI integrations
Transform your project management with intelligent automation by connecting Jira Cloud Platform and Google Gemini AI through Make. Automatically route tickets and issues to advanced AI for instant analysis, smart categorization, and intelligent insights—eliminating manual work while improving your team's decision-making and productivity.
Triggers when a ticket event occurs.
Triggers when an issue is created or updated.
Creates a new file search store.
Deletes a file from a selected files search store.
Deletes a file search store.
Extracts structured data from text or files.
Generates an image.
Generates a response for the provided input.
Generates a video.
Returns detailed information about a file in a file search store.
Retrieves details about a file search store.
Performs an arbitrary authorized API call.
Generates a response based on a simple text prompt.
Uploads a file so it can be used in the completions or in file search stores.
Returns a list of file search stores.
Returns a list of files from a selected file search store.
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Build your Jira Cloud Platform and Google Gemini AI integrations.
Connect Google Gemini AI and Jira Cloud Platform through Make's automation platform to use artificial intelligence directly within your project workflows. Google Gemini AI acts as a trigger, automatically detecting events such as new tickets, updated issues, or status changes. When these triggers activate, Jira Cloud Platform performs actions including analyzing ticket content, generating intelligent responses, categorizing issues, creating documentation summaries, and providing AI-powered insights. This integration enables automated workflows where Google Gemini AI events immediately route information to Jira Cloud Platform for sentiment analysis, content generation, or predictive analysis, eliminating manual data processing and improving decision-making processes.
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 options for a custom select field.
Creates a component.
Creates a project version.
Creates a new file search store.
Creates a new issue.
Popular Jira Cloud Platform and Google Gemini AI workflows.
Looking to get more out of Jira Cloud Platform and Google Gemini AI? With Make you can visually integrate Jira Cloud Platform and Google Gemini AI into any workflow to save time and resources — no coding required. Try any of these templates in just a few clicks.
How to setup Jira Cloud Platform and Google Gemini AI in 5 easy steps
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 to Google Cloud Platform, create a new project by giving it a name and location, then make sure it's selected from the dropdown menu at the top of the page. This project acts as the home base for your Google Gemini AI connection. Once it's set up, you'll be able to generate the special key that lets Make communicate with Google Gemini AI in your automations.
Get your API keys
To connect both apps to Make, you'll need special access keys from each service. For Google Gemini AI, visit Google AI Studio and create an API key linked to your Google Cloud project. For JIRA, go to your JIRA account settings and create an API token by giving it a label. These keys work like passwords that allow Make to securely access your apps. Make sure to copy and save both keys immediately after creating them, as you won't be able to see them again once you close the window.
Connect your apps in Make
Once you have your API keys, log in to Make and add modules for Google Gemini AI and JIRA to your scenario. Click 'Create a connection' or 'Add' next to the connection field in each module. You can give each connection a name to help you remember what it's for. For Google Gemini AI, paste your API key and save. For JIRA, enter your JIRA Service URL, username, and the API token you created. Click 'Save' for each connection, and both apps will now be linked to Make and ready to work together.
Build your automation with modules
With your connections established, you can start building your automation by adding and arranging modules. Modules are like building blocks that perform specific tasks, such as watching for new JIRA issues or analyzing text with Google Gemini AI. Browse the available options and add the modules you need. Arrange your modules in the order you want actions to happen. For example, you might set up JIRA to watch for new issues, then send that information to Google Gemini AI for processing. Configure each module with the specific settings you want to control what it does.
Test and activate your automation
Before letting your automation run automatically, test it to make sure everything works correctly. Run your scenario once and check that data flows properly between JIRA and Google Gemini AI, and that all actions complete as expected. If you see any errors, double-check your connection settings and API keys. Once everything tests successfully, activate your scenario to put it into action. Your automation will now run automatically based on your triggers, and you can monitor it through Make's logs to ensure it continues working smoothly over time.
Transform your workflow with AI-powered Jira automation
Combine Jira Cloud Platform with Google Gemini AI to automate issue analysis, generate smart summaries, and create intelligent responses that improve project management and increase team productivity.
Automatically analyze Jira issue descriptions using Gemini AI to intelligently categorize, tag, and prioritize tickets based on content understanding and sentiment analysis.
Generate concise summaries of complex Jira issues, comments, and project updates using Gemini's language capabilities to help teams quickly understand context without reading lengthy threads.
Use Gemini AI to automatically generate contextual comment responses and resolution suggestions for Jira tickets, reducing response time and improving support quality.
Transform Jira project data, sprint reports, and user stories into comprehensive documentation, release notes, or status reports using Gemini's text generation capabilities.
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