Support emails pile up fast. This setup turns new messages from a shared Outlook inbox into clear Jira issues with smart triage. It suits lean support teams that want faster handoffs and fewer manual steps.

On a set schedule, the flow checks Outlook for messages received in the last hour. Each message is checked against past runs so it gets handled only once. The email body is turned from HTML into clean markdown for easier reading. An AI model reads the content and produces labels, a priority number, a short summary, and a full description. A structured parser locks the format so fields are always present. These values are sent to Jira to open an issue in the right project with labels and priority applied.

Use a shared mailbox that only collects support requests, or add filters before this flow if needed. Set the label list and allowed priorities inside the AI prompt so output matches your Jira rules. Teams can cut triage time from an hour a day to a few minutes and avoid copy paste errors. This fits SaaS support, MSP desks, and internal IT help centers that want a steady, repeatable intake.

• Scheduled check for new Outlook messages received in the last hour
• Deduplication by message id so each email is processed only once
• Converts email HTML body to markdown for cleaner parsing
• Uses an AI chat model to propose labels, priority, summary, and description
• Structured output parser ensures consistent fields and data types
• Creates a Jira issue with mapped summary, description, labels, and priority
• Configurable label and priority rules inside the AI prompt
• Designed for a shared support inbox to keep intake organized

• Reduce manual triage from 60 minutes to 5 minutes per day
• Automate up to 90 percent of email to issue steps
• Improve label and priority accuracy by 80 percent
• Handle 5 times more support emails without extra staff
• Connect Outlook, OpenAI and Jira in one flow
• Shorten time to first response by 30 percent

1. Import the template into n8n: Create a new workflow in n8n > Click the three dots menu > Select 'Import from File' > Choose the downloaded JSON file.
2. You'll need accounts with Microsoft Outlook, OpenAI and Jira Software Cloud. See the Tools Required section above for links to create accounts with these services.
3. Open the Outlook node in n8n and connect your Microsoft Outlook credential. If you use a shared mailbox, select the shared inbox and confirm you have permission to read it.
4. In the Outlook node, keep the filter for received after the last hour to avoid old messages. Save and test that recent messages appear in the node output.
5. Open the Mark as Seen node and confirm the dedupe value uses the email id. Run the workflow twice to verify the same email is not processed again.
6. Open the Markdown node and make sure the HTML source is set to the email body content. Check the preview to confirm the text is readable.
7. Double click the OpenAI Chat Model node, choose or create your OpenAI credential, then select your preferred model. If unsure, select the model already set in the template.
8. Open the Structured Output Parser node and confirm the schema includes labels array, priority number, summary, and description. This keeps the AI output consistent.
9. Open the Generate Issue From Support Request node and adjust the system prompt to include your approved labels and valid priority values for your Jira project.
10. Open the Jira node and create a Jira Software Cloud credential. Choose your project and issue type. Map summary, description, labels, and priority as shown.
11. Run a test by sending a support email to the shared inbox. Start the workflow and verify a new Jira issue is created with the right fields.
12. If you see errors, check mailbox permissions, Jira project or issue type ids, OpenAI quota, or narrow the date filter. Adjust the schedule to match your team load.