Automate Email Replies with n8n and AI-Powered Summarization

Opening Problem Statement

Meet Laura, a customer support manager at a fast-growing e-commerce company. Every day, she receives dozens of emails requiring detailed, professional responses. Her team spends hours just reading, summarizing, and drafting replies, often risking delays or inconsistencies that frustrate customers and waste valuable time. Manual email management here costs the company hundreds of work hours monthly, increasing response times and reducing overall customer satisfaction.

What if Laura could completely automate the tedious parts of this process? Imagine her inbox automatically processing incoming emails, summarizing key points, drafting professional replies based on company knowledge, and sending those responses after a quick approval step. This workflow will save her team time—up to 5 hours daily—and reduce human error in handling communications.

What This Automation Does

This specific n8n workflow automates business email management by leveraging multiple powerful nodes. When an email arrives, it is automatically read, converted, analyzed, summarized, and a reply is generated based on company data and AI insights.

• Automated Email Reading: Using the Email Trigger (IMAP) node, the workflow detects and fetches new incoming emails from the mailbox seamlessly.
• Email Content Conversion: The Markdown node converts the raw email HTML to markdown for better context understanding by AI models.
• Email Summarization: The Email Summarization Chain node generates a concise summary (max 100 words) of the email content, clearing excess noise for quicker processing.
• Intelligent Email Writing: The Write Email agent node uses AI (OpenAI GPT models) and vector search (Qdrant) to draft a professional, context-aware response.
• Human Feedback Classification: Before sending, a Text Classifier node waits for human feedback classifying the draft as Approved or Declined, enabling review iterations.
• Sending Responses: Finally, the Send Email node dispatches the composed email back to the recipient, using SMTP configured credentials.

This automation is unique because it combines retrieval-augmented generation (RAG) powered by a vector database with AI summarization and text classification to ensure email replies are precise, factual, and reviewed before sending.

Prerequisites ⚙️

• n8n account with workflow execution capabilities (self-hosting optional via platforms like Hostinger)
• Email account configured for IMAP to trigger incoming emails
• SMTP email account to send automated replies
• Gmail account with OAuth2 for sending email drafts requiring review
• OpenAI API key for accessing GPT and embeddings models
• Qdrant vector database account configured for storing and retrieving company knowledge
• Google Drive account (optional) if you choose to upload and vectorize documents for Qdrant

Step-by-Step Guide ✏️

Step 1: Set Up the Email Trigger with IMAP

Navigate to the Email Trigger (IMAP) node in your n8n editor.

Click the node → Select your IMAP credentials for your business email account (e.g., [email protected]).

This node continuously checks your inbox for new messages. Upon receiving an email, it outputs the raw content downstream.

Common mistake: Forgetting to use correct IMAP server details or credentials causes triggering failures.

Step 2: Convert Email Content to Markdown

Click the Markdown node connected right after the Email Trigger.

Set the parameter html to ={{ $json.textHtml }} to convert the incoming email HTML content into markdown for easy analysis by the AI nodes.

You should see the raw HTML email getting converted to readable markdown format here.

Common mistake: Not referencing the correct input field could result in empty or malformed markdown output.

Step 3: Summarize the Email Content

Open the Email Summarization Chain node.

This LangChain summarization chain takes the markdown content, instructing the AI to write a concise summary up to 100 words using the configured prompt.

Verify the prompt configuration to ensure it matches the summary instructions and word limit.

This step distills important email info, simplifying subsequent response drafting.

Step 4: Generate Context-Aware Email Replies Using AI

Find the Write email agent node.

This node uses an OpenAI language model with assistance from the Qdrant Vector Store to retrieve relevant company info that helps craft accurate replies.

The prompt requests a professional, concise response no longer than 100 words.

Tips: Ensure your API keys and Qdrant connection are active to avoid empty or generic replies.

Step 5: Save Draft Replies for Human Review

After generating the draft, the Edit Fields node assigns the AI response to an email field.

The Gmail node then sends this draft to a Gmail address where your team can read, approve, or request edits.

This step uses Gmail’s special “send and wait for response” feature to facilitate asynchronous feedback.

Step 6: Classify Feedback from Human Reviewer

The Text Classifier node evaluates the incoming human feedback and classifies it as “Approved” or “Declined” based on predefined categories.

If the classification result is “Declined,” the Email Reviewer agent modifies the draft accordingly and resubmits it for review.

Step 7: Send the Final Approved Email

Once the text classifier approves the draft, the Send Email node automatically sends the final email via SMTP to the original sender.

The workflow closes the loop by replying to the original inquiry with a professional, AI-enhanced answer.

Step 8 (Optional): Maintain Company Knowledge in Qdrant

Use the HTTP Request nodes (“Create collection” and “Refresh collection”) for managing your Qdrant collections.

Upload documents from Google Drive via the Get folder and Download Files nodes, then vectorize with Embeddings OpenAI and insert them into Qdrant with the Qdrant Vector Store1 node.

This step keeps your company data updated, enhancing the reply quality.

Customizations ✏️

• Adjust Summarization Length: In the Email Summarization Chain node, modify the prompt to summarize emails into a different word or character count depending on your preferences.
• Change Email Sender Address: Edit the Send Email node’s fromEmail field to use a different email account for sending replies.
• Expand Vector Store Scope: Add more document sources in Google Drive or update Qdrant collections regularly to keep your AI responses relevant and comprehensive.
• Switch AI Models: Modify the model used in the OpenAI nodes (e.g., switch to GPT-4 or GPT-3.5-turbo) for different balance of speed and quality.
• Enhance Feedback Classification: Customize the Text Classifier node categories and system prompt to capture more nuanced human feedback types.

Troubleshooting 🔧

Problem: “IMAP trigger never fires when new emails arrive.”
Cause: Incorrect IMAP credentials or server settings.
Solution: Re-check IMAP credentials under node settings, confirm with your email provider’s IMAP configuration, and test connection in n8n.

Problem: “AI-generated emails are generic or irrelevant.”
Cause: Vector store not updated with relevant company data or OpenAI keys misconfigured.
Solution: Ensure Qdrant collection is refreshed and filled with pertinent documents. Verify OpenAI API credentials and usage limits.

Problem: “Human feedback classification fails or misclassifies.”
Cause: Inadequate prompt tuning or ambiguous categories.
Solution: Refine Text Classifier prompts and categories to better capture feedback intent.

Pre-Production Checklist ✅

• Verify IMAP and SMTP credentials work correctly.
• Test Qdrant vector store connection and ensure your collections are up-to-date.
• Confirm OpenAI API key is active and has available quota.
• Run manual tests by sending emails to the trigger mailbox.
• Check that drafts sent to Gmail for review are received and feedback classification operates.

Deployment Guide

Activate the workflow in n8n and ensure all credentials are set to active mode.

Monitor execution logs for errors periodically, especially after initial launch.

Use n8n’s built-in error handling to retry failed executions or send alerts if needed.

FAQs

Can I use Outlook instead of Gmail for draft reviews?
Currently, the workflow relies on Gmail’s “send and wait for response” feature, so Gmail is required for feedback collection.

Does this automation consume OpenAI API credits?
Yes, each summarization and reply generation counts as API calls, so monitor your usage accordingly.

Is my email data secure in this workflow?
Data is processed within your n8n instance and connected APIs. Ensure secure API key storage and restrict workflow access.

Conclusion

By following this guide, you’ve built an advanced email management system that harnesses n8n automation, AI summarization, vector search, and human-in-the-loop review to drastically reduce manual email handling time and improve response quality.

This saves teams like Laura’s up to 5 hours daily, freeing up valuable resources and boosting customer satisfaction.

Next, consider expanding this setup to automate multi-channel support (chatbots, SMS), integrate CRM updates based on email conversations, or implement ticket tracking automation for a full customer service ecosystem.

Remember, automation with AI is not just about saving time but empowering your team to focus on what matters most.