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.
Generate vector representations (embeddings) for the text or file you provide.
Generate high-quality, stereo audio from text prompts or from images.
Generates an audio file based on text input and settings.
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 text responses from prompts without requiring an account or connection.
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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FAQ
By integrating Jira Cloud Platform with Google Gemini AI through Make, you can automate intelligent project management tasks such as automatically generating ticket descriptions, summarizing sprint reports, creating release notes from completed issues, and translating ticket content for global teams. Gemini AI can analyze your Jira data to provide insights, suggest priorities, or even generate code snippets for technical tickets. This integration eliminates manual documentation work and increases team productivity by leveraging AI-powered automation directly within your project management workflow.
Make enables powerful automation scenarios combining Jira and Gemini AI, such as: automatically generating detailed user stories from brief requirements, creating comprehensive test cases based on feature descriptions, summarizing comment threads on complex issues, translating tickets for international teams, analyzing bug reports to suggest potential solutions, generating project status reports from sprint data, and creating documentation from completed tasks. These automations run in the background, saving hours of manual work while maintaining high-quality outputs through Gemini's advanced language capabilities.
No coding skills are required. Make provides a visual, drag-and-drop interface that makes it straightforward to connect Jira Cloud Platform with Google Gemini AI. You select triggers from Jira (like new issues or updated tickets), connect them to Gemini AI actions (such as text generation or analysis), and map the data between applications using Make's intuitive interface. Make handles all the technical complexities of API connections and data formatting, allowing you to create sophisticated automations in minutes without writing a single line of code.
Make implements enterprise-grade security measures to protect your data when integrating Jira Cloud Platform with Google Gemini AI. All data transfers are encrypted using industry-standard protocols, and Make uses secure OAuth authentication for both applications, meaning your credentials are never directly exposed. You maintain full control over what data is shared between applications, and Make complies with major data protection regulations including GDPR. Additionally, Make's transparent permission system lets you define exactly which Jira projects and data Gemini AI can access, ensuring your sensitive project information remains secure throughout the automation process.
A scenario represents a workflow or a project of your own creation, and it is made up of a series of modules that automate apps and services. Creating a scenario allows you to transfer and transform data between apps and services via these modules to automate anything and improve the way you work.
Modules are the main building blocks of automation in Make. Modules represent actions that Make performs with an app, like creating, updating, or deleting data.
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