Automate customer support issue resolution using AI text classifier

This n8n template is designed to assist and improve customer support team member capacity by automating the resolution of long-lived and forgotten JIRA issues.

How it works

• Schedule Trigger runs daily to check for long-lived unresolved issues and imports them into the workflow.
• Each Issue is handled as a separate subworkflow by using an execute workflow node. This allows parallel processing.
• A report is generated from the issue using its comment history allowing the issue to be classified by AI - determining the state and progress of the issue.
• If determined to be resolved, sentiment analysis is performed to track customer satisfaction. If negative, a slack message is sent to escalate, otherwise the issue is closed automatically.
• If no response has been initiated, an AI agent will attempt to search and resolve the issue itself using similar resolved issues or from the notion database. If a solution is found, it is posted to the issue and closed.
• If the issue is blocked and waiting for responses, then a reminder message is added.

How to use

• This template searches for JIRA issues which are older than 7 days which are not in the "Done" status. Ensure there are some issues that meet this criteria otherwise adjust the search query to suit.
• Works best if you frequently have long-lived issues that need resolving.
• Ensure the notion tool is configured as to not read documents you didn't intend it to ie. private and/or internal documentation.

Requirements

• JIRA for issues management
• OpenAI for LLM
• Slack for notifications

Customising this workflow

• Why not try classifying issues as they are created? One use-case may be for quality control such as ensuring reporting criteria is adhered to, summarising and rephrasing issue for easier reading or adjusting priority.