Customer Support Channel and Ticketing System with Slack and Linear
This n8n workflow demonstrates how to create a really simple yet effective customer support channel and pipeline by combining Slack, Linear and AI tools.
Built on n8n's ability to integrate anything, this workflow is intended for small support teams who want to maximise re-use of the tools they already have with an interface which is doesn't require any onboarding.
Read the blog post here: https://blog.n8n.io/automated-customer-support-tickets-with-n8n-slack-linear-and-ai/
How it works
- The workflow is connected to a slack channel setup with the customer to capture support issues.
- Only messages which are tagged with a "✅" reaction are captured by the workflow. Messages are tagged by the support team in the channel.
- Each captured support issue is sent to the AI model to classify, prioritise and rewrite into a support ticket.
- The generated support ticket is uploaded to Linear for the support team to investigate and track.
- Support team is able to report back to the user via the channel when issue is fixed.
Requirements
- Slack channel to be monitored
- Linear account and project
Customising this workflow
Don't have Linear? This workflow can work just as well with traditional ticketing systems like JIRA.
Customer Support Channel and Ticketing System with Slack and Linear
This n8n workflow automates the process of creating a customer support channel in Slack and a corresponding ticket in Linear, based on a scheduled trigger. It leverages AI to categorize and summarize the support request before creating the Linear issue.
What it does
This workflow streamlines the customer support process by:
- Triggering on a Schedule: The workflow starts at predefined intervals.
- Generating a Support Request (Simulated): It simulates a customer support request, including a subject and description, which would typically come from an external source.
- Analyzing with AI: It uses an OpenAI Chat Model with a Basic LLM Chain and a Structured Output Parser to:
- Categorize the support request (e.g., "Bug", "Feature Request", "Question").
- Generate a concise summary of the request.
- Determine the priority of the request (e.g., "High", "Medium", "Low").
- Conditional Routing: It checks if the AI successfully categorized the issue.
- Creating a Slack Channel: If the categorization is successful, it creates a new public Slack channel for the support request, using the AI-generated category and a unique identifier.
- Posting to Slack: It posts a message to the newly created Slack channel, including the original request details, AI-generated summary, category, and priority.
- Creating a Linear Issue: It creates a new issue in Linear, using the AI-generated summary as the title, the original description, and the AI-determined priority and category.
- Merging Data: It combines the outputs from the Slack and Linear operations.
Prerequisites/Requirements
To use this workflow, you will need:
- n8n Account/Instance: To host and run the workflow.
- OpenAI Account & API Key: For the
OpenAI Chat Modelnode to categorize and summarize support requests. - Slack Account & Credentials: To create channels and post messages.
- Linear Account & Credentials: To create and manage support tickets.
Setup/Usage
- Import the Workflow:
- Copy the provided JSON code.
- In your n8n instance, go to "Workflows" and click "New".
- Click the "Import from JSON" button and paste the copied JSON.
- Configure Credentials:
- Locate the
OpenAI Chat Modelnode and configure your OpenAI API Key credential. - Locate the
Slacknode and configure your Slack API credential. - Locate the
Linearnode and configure your Linear API credential.
- Locate the
- Configure Schedule Trigger:
- Adjust the
Schedule Triggernode to your desired interval for checking/processing support requests.
- Adjust the
- Activate the Workflow:
- Once all credentials are set and configurations are done, activate the workflow by toggling the "Active" switch in the top right corner of the n8n editor.
This workflow is designed to be a starting point and can be further customized to integrate with other services, refine AI prompts, or add more complex routing logic.
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