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Auto-assign support tickets with JIRA, Supabase and AI

n8nn8n28 modulesv1.0
JiraOpenAI

This n8n template builds a simple automation to ensure no JIRA issues go unassigned for more than a week to prevent them falling through the cracks. It uses AI to perform searching tasks against a Supabase Vector Store. This can be one way to help reduce the amount of manual work in managing the issue backlog for busy teams with little effort. How it works This template contains 2 separate flows which run continuously via schedule triggers. The first populates our Supabase vector store with re

At a glance

Auto-assign support tickets with JIRA, Supabase and AI is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects Jira, OpenAI. It's free to download. Follow the 5-step import below to go live in minutes.

Platform
n8n
Connects
Jira, OpenAI
Modules
28
Price
Free
Version
v1.0
Auto-assign support tickets with JIRA, Supabase and AI workflow diagram

About this workflow

This n8n template builds a simple automation to ensure no JIRA issues go unassigned for more than a week to prevent them falling through the cracks. It uses AI to perform searching tasks against a Supabase Vector Store. This can be one way to help reduce the amount of manual work in managing the issue backlog for busy teams with little effort. How it works This template contains 2 separate flows which run continuously via schedule triggers. The first populates our Supabase vector store with resolved issues within the last day. This helps keep our vector store up-to-date and relevant for the purpose of finding similar issues. It does this by pulling the latest resolved issues from JIRA and populating the Supabase vectorstore with carefully chosen metadata. This will come in handy later. The second flow watches for stale, unassigned issues for the purpose of aut-assigning to a relevant team member. It does this by comparing the stale issue against our vector store of resolved issues with the goal of identifying which team member would have best context regarding the issue. In a busy team, this may net a few team members as possible candidates to assign. Therefore, we can introduce additional logic to count each team member's assigned, in-progress issues. This is intended to not overload our busiest members. The team member with the least assigned issues is pressumed to have the most capacity and therefore is assigned. A comennt is left in the issue to notify the team member that they've been auto-assigned due to age of issue. How to use Modify the project and interval parameters to match those of your use-case and team members. Add additional criteria before assigning to a team member eg. department, as required. Requirements OpenAI for LLM JIRA for Issue Management Supabase for Vector Store Customising this workflow Not using JIRA or Supabase? The beauty of these AI templates are these components are entirely interchangeable with competing services. Try Linear and Qdrant instead! Auto-assigning logic is simplified in this template. Expand criteria as required for your team and organisation. eg. Might be a good idea to pull in annual leave information from HR system to prevent assigning to someone who is on currently on holiday!

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How to import this n8n workflow

  1. 1

    Download the workflow JSON file after purchase.

  2. 2

    Open n8n → click the menu → Import from File.

  3. 3

    Select the downloaded JSON and import.

  4. 4

    Set up credentials for each node that requires them.

  5. 5

    Click Execute Workflow to test, then activate.

Setup guide

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