n8n AI Tutorial: Workflow Automation with AI

June 29, 2026 · View on GitHub

Build powerful AI-powered automations with n8n's visual workflow builder.

⚡ AI Meets Automation

Why This Track Matters

n8n AI is increasingly relevant for developers working with modern AI/ML infrastructure. Build powerful AI-powered automations with n8n's visual workflow builder, and this track helps you understand the architecture, key patterns, and production considerations.

This track focuses on:

Build AI Workflows visually with n8n
Connect LLM Providers (OpenAI, Anthropic, Ollama)
Process Documents with AI extraction
Create AI Agents with tool access

🎯 What is n8n?

n8n^{View Repo} is a fair-code workflow automation platform that lets you connect anything to everything. With its AI capabilities, you can build intelligent automations that leverage LLMs, process documents, and make smart decisions.

Key Features

Feature	Description
Visual Builder	Drag-and-drop workflow creation
AI Nodes	OpenAI, Anthropic, local models
400+ Integrations	Connect any service
Self-Hostable	Full control over your data
Code When Needed	JavaScript/Python in workflows
Agents	Build AI agents with tools

Mental Model

flowchart LR
    A[Trigger] --> B[n8n Workflow]
    
    B --> C[Data Processing]
    C --> D[AI Node]
    D --> E[LLM Processing]
    
    E --> F[Decision]
    F --> G[Action 1]
    F --> H[Action 2]
    
    G --> I[Slack]
    H --> J[Database]
    H --> K[Email]
    
    classDef trigger fill:#e1f5fe,stroke:#01579b
    classDef process fill:#f3e5f5,stroke:#4a148c
    classDef ai fill:#fff3e0,stroke:#ef6c00
    classDef output fill:#e8f5e8,stroke:#1b5e20
    
    class A trigger
    class B,C process
    class D,E,F ai
    class G,H,I,J,K output

Current Snapshot (auto-updated)

repository: n8n-io/n8n
stars: about 194k
GitHub release reference: n8n@2.27.5 (checked 2026-06-29; release metadata on GitHub)

Chapter Guide

Chapter 1: Getting Started - Installation and first workflow
Chapter 2: AI Nodes - Using OpenAI, Anthropic, and local models
Chapter 3: Document AI - Processing PDFs, images, and text
Chapter 4: AI Agents - Building autonomous agents
Chapter 5: RAG Workflows - Retrieval-augmented generation
Chapter 6: Smart Decisions - AI-powered routing and logic
Chapter 7: Custom AI Tools - Extending agent capabilities
Chapter 8: Production Deployment - Scaling and monitoring

What You Will Learn

Build AI Workflows visually with n8n
Connect LLM Providers (OpenAI, Anthropic, Ollama)
Process Documents with AI extraction
Create AI Agents with tool access
Implement RAG for knowledge-based AI
Make Smart Decisions based on AI analysis
Deploy Production automations

Prerequisites

Docker (recommended) or Node.js 18+
API keys for AI providers
Basic workflow automation understanding

Quick Start

Docker

docker run -it --rm \
  --name n8n \
  -p 5678:5678 \
  -v n8n_data:/home/node/.n8n \
  n8nio/n8n

# Open http://localhost:5678

npm

npm install n8n -g
n8n start

Your First AI Workflow

Add Trigger - Webhook, Schedule, or Manual
Add AI Node - OpenAI, Anthropic, etc.
Configure Prompt - Define your AI task
Add Output - Slack, Email, Database
Activate - Run your workflow

AI Nodes Available

Node	Capability
OpenAI	GPT-4, GPT-3.5, embeddings
Anthropic	Claude 3.5, Claude 3
Ollama	Local LLM inference
AI Agent	Autonomous agents with tools
Vector Store	RAG with Pinecone, Qdrant
Document Loader	PDF, web, text processing

Example: Smart Email Responder

{
  "nodes": [
    {
      "type": "gmail-trigger",
      "parameters": {"event": "newEmail"}
    },
    {
      "type": "openai",
      "parameters": {
        "model": "gpt-4o",
        "prompt": "Classify this email and draft a response:\n\n{{$json.text}}"
      }
    },
    {
      "type": "if",
      "parameters": {
        "conditions": [{"value1": "{{$json.classification}}", "value2": "urgent"}]
      }
    },
    {
      "type": "gmail",
      "parameters": {"operation": "sendReply"}
    }
  ]
}

AI Agent Example

Trigger: Customer Support Ticket

AI Agent:
  - Tool: Search Knowledge Base
  - Tool: Check Order Status
  - Tool: Create Support Ticket
  
Logic: Agent decides which tools to use based on customer query

Output: 
  - Reply to customer
  - Update CRM
  - Notify team if escalation needed

RAG Workflow

1. Document Loader → Process PDF
2. Text Splitter → Chunk document
3. Embeddings → OpenAI embeddings
4. Vector Store → Store in Pinecone
5. On Query:
   - Search vector store
   - Pass context to LLM
   - Generate response

Integrations + AI

Integration	AI Use Case
Slack	AI-powered responses
Gmail	Smart email categorization
Notion	AI content generation
Airtable	Data enrichment
GitHub	PR review automation
Stripe	Fraud detection

Learning Path

🟢 Beginner Track

Chapters 1-3: Setup and basic AI nodes
Build simple AI automations

🟡 Intermediate Track

Chapters 4-6: Agents, RAG, and decisions
Create intelligent workflows

🔴 Advanced Track

Chapters 7-8: Custom tools and production
Scale enterprise AI automation

Ready to automate with AI? Let's begin with Chapter 1: Getting Started!

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Full Chapter Map

Source References

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