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AI Agents

Process email messages intelligently with AI agent

9 nodes 591 212 Automatic trigger
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Workflow Description

This workflow connects Gmail to an AI-powered agent built on OpenAI to automatically read, analyze, and respond to incoming emails intelligently. The agent retains conversation history to provide contextual and consistent replies over time.

How it works

  1. 1.Trigger captures new incoming messages from Gmail automatically
  2. 2.Email content is passed to the OpenAI-powered AI agent for analysis
  3. 3.Agent determines response strategy and uses Gmail tool to send reply
  4. 4.Conversation context and prior responses are stored in memory buffer
  5. 5.Optional wait step prevents rate limiting between automated actions

Use cases

  • Automatically respond to common inquiries with personalized, context-aware answers
  • Classify and prioritize incoming emails based on content and urgency
  • Generate executive summaries of important messages and forward to management

Requirements

  • Active Gmail account with read and write permissions enabled
  • Valid OpenAI API key with sufficient usage quota
  • Basic understanding of AI agents and context-aware conversation flow

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

Gmail OpenAI AI Agent Memory Wait

Details

Trigger Automatic trigger
Nodes 9
Apps 5
Views 591
Downloads 212

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (9)

/

Gmail Trigger

Gmail

#1

OpenAI Chat Model1

OpenAI

#2

Gmail - read labels

Gmail

#3

Gmail - get message

Gmail

#4

Gmail - add label to message

Gmail

#5

Gmail - create label

Gmail

#6

Gmail labelling agent

Agent

#7

Window Buffer Memory

Memory Buffer Window

#8

Wait

Wait

#9

Sticky Note

Sticky Note

#10

Sticky Note1

Sticky Note

#11

Sticky Note2

Sticky Note

#12

Sticky Note3

Sticky Note

#13
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