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Auto-reply to Udemy student Q&A with Mistral AI and Google Sheets

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Auto-reply to Udemy student Q&A with Mistral AI and Google Sheets preview
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1. Workflow Overview

Stop Drowning in Repetitive Udemy Student Questions If you teach on Udemy at any meaningful scale, you already know the problem: 80% of student messages are variations of the same handful of questi...

Best for

  • Support Chatbot automation workflows
  • AI Chatbot automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.scheduletrigger, n8n-nodes-globals.globalconstants, n8n-nodes-base.httprequest, n8n-nodes-base.splitout, n8n-nodes-base.splitinbatches, n8n-nodes-base.googlesheets, n8n-nodes-base.if, n8n-nodes-base.code

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Hesham Mashhour.

Original n8n.io source

1.1 Workflow description

Title
Auto-reply to Udemy student Q&A with Mistral AI and Google Sheets
Workflow name
Auto-reply to Udemy student Q&A with Mistral AI and Google Sheets

Stop Drowning in Repetitive Udemy Student Questions

If you teach on Udemy at any meaningful scale, you already know the problem: 80% of student messages are variations of the same handful of questions, but every one of them needs a thoughtful reply to keep your response rate up and your reviews healthy. Meanwhile, the actually important messages — students asking about other courses you offer, career advice, coaching opportunities — get buried in the noise and answered late, if at all.

This workflow fixes that. It connects to Udemy's Instructor API, pulls every unreplied message thread, and routes each one to one of two destinations:

  • Auto-reply — for technical questions, course clarifications, greetings, and routine support, an AI agent (Mistral Large primary, Claude Sonnet 4.5 fallback) generates a context-aware Markdown response in your voice and posts it back to Udemy automatically
  • Escalate to you — for sales opportunities, refund requests, complaints, personal questions, and anything genuinely ambiguous, you get an email with the message and a deep link to your inbox so you can respond personally

The result: you reply faster, students get help quicker, and you never miss a high-value conversation that could turn into another course enrollment.

What's Inside

  • Smart routing logic — A structured-output AI agent decides between auto-reply and escalation based on 18+ explicit rules covering sales triggers, complaint detection, scope ambiguity, and conversation openers
  • Full conversation context — Pulls the entire thread history into the AI's prompt so replies feel continuous, not robotic
  • Per-thread memory isolation — Redis-backed chat memory with unique session keys per conversation, so threads never bleed into each other
  • Built-in research — Jina AI deep research tool lets the agent verify technical claims before answering instead of hallucinating
  • Audit trail — Every message, reply, AI confidence score, and escalation reason is logged to Google Sheets for review and quality control
  • Markdown output — Replies post in clean Markdown that Udemy renders natively (no HTML soup)
  • Self-loop prevention — Skips threads where you replied last to avoid awkward double-responses

Use Case

Built for Udemy instructors with growing course catalogs who want to maintain personal, high-quality Q&A responsiveness without spending hours per week typing the same answers. Especially valuable if you run multiple courses, sell premium offerings (coaching, consulting, advanced courses), or care about your response-rate metric on Udemy's instructor dashboard.

Required Services

  • Udemy Instructor API access (free, available to all instructors)
  • Mistral Cloud, Anthropic, OpenAI, and Jina AI accounts (combined cost: ~$0.001–0.005 per message)
  • Google Sheets, Gmail, and a Redis instance (free tiers fine)

Comprehensive setup instructions are baked into the workflow as sticky notes — column schema, global constants, and credential mapping all documented inline.

Tags

udemy ai-agent customer-support mistral claude gpt google-sheets gmail redis automation online-teaching creator-economy

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Trigger: Scheduled Run

Type / Role
n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices
Version 1.3

Block 2 - Load Global Constants

Type / Role
n8n-nodes-globals.globalConstants - globalConstants
Config choices
Version 1

Block 3 - Fetch Unreplied Threads (Udemy API)

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.3

Block 4 - Split Threads Array

Type / Role
n8n-nodes-base.splitOut - splitOut
Config choices
Version 1

Block 5 - Loop Through Each Thread

Type / Role
n8n-nodes-base.splitInBatches - splitInBatches
Config choices
Version 3

Block 6 - Fetch Full Thread History

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.3

Block 7 - Log New Message to Sheet

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.7

Block 8 - Skip if Instructor Sent Last Message

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.3

Block 9 - Generate Redis Session Key

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 10 - AI Agent: Reply or Escalate

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3.1

Block 11 - Memory: Redis Chat

Type / Role
@n8n/n8n-nodes-langchain.memoryRedisChat - memoryRedisChat
Config choices
Version 1.5

Block 12 - LLM: Mistral Large (Primary)

Type / Role
@n8n/n8n-nodes-langchain.lmChatMistralCloud - lmChatMistralCloud
Config choices
Version 1

Block 13 - LLM: Claude Sonnet 4.5 (Fallback)

Type / Role
@n8n/n8n-nodes-langchain.lmChatAnthropic - lmChatAnthropic
Config choices
Version 1.3

Block 14 - Tool: Jina Deep Research

Type / Role
n8n-nodes-base.jinaAiTool - jinaAiTool
Config choices
Version 1

Block 15 - Parser: Structured JSON Output

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 16 - LLM: GPT-4.1-mini (Parser)

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.3

Block 17 - Branch: Auto-Reply or Escalate?

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.3

Block 18 - Mark Row as Escalated

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.7

Block 19 - Save AI Response to Sheet

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.7

Block 20 - Post AI Reply to Udemy

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.3

Block 21 - Email Instructor for Manual Reply

Type / Role
n8n-nodes-base.gmail - gmail
Config choices
Version 2.2

Block 22 - Note: Overview

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 23 - Note: Setup Instructions

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 24 - Note: Google Sheet Schema

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Showing the first 24 of 29 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Auto-reply to Udemy student Q&A with Mistral AI and Google Sheets
Complexity advanced
Nodes 29
Categories Support Chatbot, AI Chatbot
Author Hesham Mashhour
Published 26 Apr 2026

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/15311/15311.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Auto-reply to Udemy student Q&A with Mistral AI and Google Sheets do?

Stop Drowning in Repetitive Udemy Student Questions If you teach on Udemy at any meaningful scale, you already know the problem: 80% of student messages are variations of the same handful of questi...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Support Chatbot, AI Chatbot use case.