This article provides a complete, practical walkthrough of the Markdown Stickynote Send n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Simple setup in 5-15 minutes. One‑time purchase: €9.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   AI-Powered Human-in-the-Loop Email Workflow Using n8n, LangChain, and OpenAI
   
   Meta Description:
   Discover how to automate professional email responses with a human-in-the-loop system using n8n, LangChain, and OpenAI. Learn how this workflow uses IMAP, summarization, GPT response generation, and review approval before replying to emails.
   
   Keywords:
   n8n workflow automation, AI email assistant, human-in-the-loop, IMAP email parsing, OpenAI GPT-4o-mini, LangChain summarization, AI email summarizer, automated business email reply, DeepSeek API integration, SMTP automation, smart email response
   
   Third-Party APIs Used:
   
   - OpenAI API (GPT-4o-mini language model)
   - DeepSeek API (language model)
   - LangChain (via n8n LangChain nodes, for summarization and agent functionality)
   - IMAP (for reading emails)
   - SMTP (for sending emails)
   
   Article:
   
   Automating Business Email Responses with AI and a Human Touch: A Simple n8n Workflow
   
   Email has long been the backbone of professional communication, but managing a growing volume of inquiries, requests, and responses can be both time-consuming and error-prone. Enter n8n—a powerful open-source workflow automation tool that, when combined with AI and smart summarization chains, transforms how emails are handled. In this article, we break down a practical n8n workflow designed to intelligently read, summarize, generate, and respond to emails—while still keeping a human in the loop for final review and approval.
   
   This workflow is titled “Very simple Human in the loop system email with AI e IMAP” and provides an automated yet safe pipeline for managing incoming messages. It integrates several key technologies, including OpenAI’s GPT-4o-mini, DeepSeek’s language model, LangChain summarization chains, and traditional email protocols (IMAP & SMTP).
   
   Let’s break it down step-by-step:
   
   1. Email Trigger: IMAP Email Fetching
   The process begins with the “Email Trigger (IMAP)” node. This node monitors a specific inbox (connected via IMAP—info@n3witalia.com in this case) and pulls in any new incoming messages. This serves as the entry point for the flow, acting as a real-time alert system to process emails as soon as they arrive.
   
   2. Markdown Conversion for Enhanced AI Interpretation
   Next, an “Markdown” node converts the HTML email body into Markdown format. This step is critical because Markdown formatting is more machine-readable and structured, which helps language models better interpret and summarize the content.
   
   3. Summarization of Email Content with LangChain
   The converted Markdown is then fed into the “Email Summarization Chain,” powered by the LangChain plugin and DeepSeek language model. The summarization uses a defined prompt that instructs the model to produce a concise summary (max 100 words). This abstraction streamlines further AI processing by stripping away insignificant noise from long-form emails.
   
   4. AI-Generated Response Using GPT-4o-mini
   The core of the workflow lies in generating a professional, context-aware reply. The summary output flows into the “Write email” LangChain agent node. This node prompts OpenAI’s GPT-4o-mini model to draft a reply with specific rules:
   - Respond professionally
   - Keep it under 100 words
   - Output only the email body (no subject line)
   This ensures precise, business-appropriate messages optimized for quick understanding and action.
   
   5. Preparing the Email for Human Approval
   Before any AI-generated response is sent, the “Set Email text” node formats the reply. Then, a critical “Approve Email” node kicks in, combining the original message with the proposed response and sending it internally (to the team at info@n3witalia.com) via SMTP. The subject line is prefixed with “[Approval Required],” and the email body shows both the received content and the AI’s proposed reply.
   
   6. Human-in-the-Loop Review and Approval
   An “Approved?” decision node awaits human feedback. If the email is marked as approved (i.e., someone manually flags it via an outbound link or interface), the workflow continues. If not, the email isn’t sent—ensuring a safety net before automatic responses go live.
   
   7. Final Email Dispatch
   Once approved, the “Send Email” node is triggered, completing the loop. The reply is sent directly to the original sender via SMTP, ensuring the recipient receives a thoughtful, clear, and correct response—crafted by AI and double-checked by a human.
   
   Why It Matters
   This workflow exemplifies a modern blend of AI and responsible automation. Instead of removing humans from the communication loop altogether, it uses AI to do the heavy lifting while empowering humans to make final decisions—ideal for customer service, support, or sales inquiries.
   
   Key Benefits:
   
   - Saves time on reading and responding to emails
   - Maintains professionalism with tailored AI replies
   - Provides control via a human-in-the-loop checkpoint
   - Supports integrations with Gmail, Outlook, and other IMAP-compatible services
   - Easily customizable and scalable via n8n
   
   Closing Thoughts
   As we move into an era where AI increasingly augments business operations, hybrid workflows like this one help enterprises evolve without losing the human essence. By integrating tools like LangChain, OpenAI, DeepSeek, and IMAP/SMTP into n8n, you create an intelligent yet accountable email system that can serve as the foundation for more complex customer engagement pipelines.
   
   Whether managing a customer support inbox, handling sales inquiries, or maintaining executive communications, this n8n workflow offers a practical, scalable, and secure approach to optimizing email communication with AI-powered efficiency.
   
   Ready to build something similar? n8n’s drag-and-drop interface and powerful plugin ecosystem make it accessible to teams of all technical levels. Just don’t forget to keep the human touch—that’s still your best competitive edge.
   
   — End —

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.