Automated Slack IT helpdesk with GPT, Supabase vector search, and JIRA ticketing

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

Who is this for?

IT teams and support organizations looking to automate Level 1 support with AI-powered assistance while maintaining proper ticket management workflows.

What problem does this solve?

Eliminates repetitive manual support tasks by providing instant, context-aware assistance that references organizational knowledge and creates structured tickets when needed.

What this workflow does

• RAG Pipeline: Processes PDF/CSV documents into searchable vector database
• Intelligent Slack Bot: This AI-helpdesk assistant handles support requests with thread-aware conversations
• Vector Knowledge Search: Searches embedded knowledge base articles and historical case data
• JIRA Integration: Creates, searches, and manages support tickets automatically
• Emoji Reactions: Users can trigger actions (create tickets, escalate) via emoji reactions

Requirements

Required Accounts:

• n8n Cloud or self-hosted instance
• Slack workspace with admin access
• Supabase account (vector database)
• JIRA Cloud instance
• OpenAI API key

Technical Prerequisites:

• Basic n8n workflow knowledge
• Slack app creation experience
• Understanding of vector databases

Setup Steps

1. Slack App Configuration

• Create new Slack app with Bot Token Scopes: app_mentions:read, channels:history, channels:read, groups:history, groups:read, im:history, im:read, mpim:history, mpim:read, users:read
• Configure Event Subscriptions: app_mention, message.channels, message.groups, reaction_added
• Set Request URL to your n8n Slack Trigger webhook

2. Supabase Vector Database Setup

• Create new Supabase project
• Enable pgvector extension
• Create documents table with vector column (1536 dimensions for OpenAI embeddings)
• Configure RLS policies for secure access

3. JIRA Configuration

• Generate API token from JIRA Cloud
• Create helpdesk project with appropriate issue types
• Note project ID and issue type IDs for workflow configuration

4. n8n Workflow Configuration

• Import workflow and configure credentials
• Update Slack channel IDs in trigger nodes
• Set OpenAI API key in all OpenAI nodes
• Configure Supabase connection in vector store nodes
• Update JIRA project settings in MCP server nodes

5. Knowledge Base Data Format

Supported file formats: PDF, CSV CSV Structure: Structure your data with columns, but not limited to, Ticket#, Issue Description, Issue Summary, Resolution Provided, Case Status, Contact User PDF Content: Technical documentation, troubleshooting guides, policy documents

Upload documents via the form trigger to automatically embed in vector database.

Customization Options

AI Agent Behavior

• Modify system prompt in AIHelpdesk Agent node
• Adjust conversation memory window (default: 20 messages)
• Change AI model (GPT-4o, GPT-3.5-turbo, etc.)

Reaction Mappings

• Customize emoji-to-action mappings in Reaction Handler code
• Add new reaction types for department-specific workflows
• Configure escalation rules and priority levels

JIRA Integration

• Customize ticket templates and fields
• Add auto-assignment rules based on issue type
• Configure SLA and priority mappings

Vector Search

• Adjust similarity thresholds for knowledge retrieval
• Modify search result limits and relevance scoring
• Add metadata filtering for departmental knowledge bases

Advanced Features

• Thread-aware conversation memory
• Automatic bot loop prevention
• Context-preserving ticket creation
• Multi-modal file processing (PDF + CSV)
• Scalable MCP architecture for tool integration

Use Cases

• Level 1 IT Support: Automate common troubleshooting workflows
• Employee Onboarding: Answer policy and procedure questions
• Internal Help Desk: Route and track internal service requests
• Knowledge Management: Make organizational knowledge searchable and actionable

Template includes

• Complete Slack integration with thread support
• RAG pipeline for document processing
• Vector similarity search implementation
• JIRA ticket lifecycle management
• Emoji reaction-based user interactions
• Comprehensive error handling and validation