Categorize and Label Incoming Gmail Emails Automatically with GPT-4o mini

Description

Sort New Gmail messages by category with AI 👥 Who's it for This workflow is perfect for individuals or teams who receive a high volume of emails 📥 and want to automatically organize them into Gmail labels 🏷️ using AI. No coding required! For sorting existing emails messages in your gmail inbox, please use this free workflow: Categorize and Label Existing Gmail Emails Automatically with GPT-4o mini. 🤖 What it does It automatically processes new Gmail emails, skips those that already have labels, sends the content to an AI Agent powered by GPT-4o mini 🧠, and applies a relevant label based on the content. All labels must exist in Gmail beforehand. ⚙️ How it works 📬 Gmail Trigger – Activates on new email received. 🚫 Filter – Skips emails that already have a label. 🧠 AI Agent (GPT-4o mini) – Analyzes the message and decides which label fits best. 🧾 Structured Output Parser – Formats the AI output into a clean JSON. 🔀 Switch Node – Routes each email to the correct label path based on the AI result. 🏷️ Gmail Nodes – Assign the Gmail label to the original email. 📋 Requirements Gmail account connected to n8n Pre-created labels in Gmail matching the AI categories OpenAI credentials with GPT-4o mini access n8n's AI Agent & Structured Output Parser nodes 🛠️ How to set up Open the workflow and adjust the trigger interval (e.g., every minute, hours or Custom using Cron ⏱️) Check that the Filter skips emails with existing labels Define your categories in the AI Agent prompt and make sure they match the Gmail labels Configure the Switch Node conditions for each category Ensure each Gmail Label Node applies the correct label Save and activate the workflow ✅ 🎨 How to customize the workflow Add or remove categories in the AI prompt & Switch Node Fine-tune prompt instructions to match your specific use case. An n8n automation workflow template by Arlin Perez.

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Categories

• Automation
• AI

Tags

• n8n
• workflow
• gmail
• ai-agent
• openai-chat-model
• structured-output-parser

Capabilities

• 4 nodes
• 513 views

Information