AI-powered student assistant for course information via Twilio SMS

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS. Given the right access to data, AI Agents are capable of planning and performing relatively...

Best for

Support Chatbot automation workflows
AI Chatbot automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.twiliotrigger, n8n-nodes-base.airtabletool, n8n-nodes-base.set, n8n-nodes-base.twilio, n8n-nodes-base.airtable, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: AI-powered student assistant for course information via Twilio SMS
Workflow name: AI-powered student assistant for course information via Twilio SMS

This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS.

Given the right access to data, AI Agents are capable of planning and performing relatively complex research tasks to get their answers. In this example, the agent must first understand the database schema, retrieve lists of values before generating it's own query to search over the database.

Checkout the example database here - https://airtable.com/appO5xvP1aUBYKyJ7/shr8jSFDaghubDOrw

How it works

A Twilio trigger gives us the ability to receive SMS input into our workflow via webhook.
The message is then directed to our AI agent who is instructed to assist the user and use the course database as reference. The database is an Airtable base.
The agent autonomously figures out which tool it needs to use and generates it's own "filter_by_formula" query to search over the available courses.
On successful search results, the Agent can then use this information to answer the user's query.
The Agent's output is logged in a second sheet of the Airtable base. We can use this later for analysis and lead gen.
Finally, the response is sent back to the user through SMS using Twilio.

How to use

Ensure your Twilio number is set to forward messages to this workflow's webhook URL.
Configure and update the course database as required. If you're not interested in courses, you can swap this out for inventory, deliveries or any other data relevant to your business.
Ask questions like:
- "Can you help me find suitable courses to fill my Wednesday mornings?"
- "Which courses are being instructed by profession Lee?"
- "I'm interested in creative arts. What courses are available which could be relevant to me?"

Requirements

Twilio for SMS receiving and sending
OpenAI for LLM and Agent
Airtable for Course Database

Customising this workflow

Add additional tools and expand the range of queries the agent is able to answer or assist with.
Not using Airtable? This technique also works with SQL databases like PostgreSQL.

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 - Twilio Trigger

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

Block 2 - Search Available Courses

Type / Role: n8n-nodes-base.airtableTool - airtableTool
Config choices: Version 2.1

Block 3 - Get Course Database Schema

Type / Role: n8n-nodes-base.airtableTool - airtableTool
Config choices: Version 2.1

Block 4 - Get User Message

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 5 - Send SMS reply

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

Block 6 - Append to Call Log

Type / Role: n8n-nodes-base.airtable - airtable
Config choices: Version 2.1

Block 7 - Course Assistant Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.8

Block 8 - Get List of Professors

Type / Role: n8n-nodes-base.airtableTool - airtableTool
Config choices: Version 2.1

Block 9 - Get List of Departments

Type / Role: n8n-nodes-base.airtableTool - airtableTool
Config choices: Version 2.1

Block 10 - Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 11 - Memory

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

Block 12 - Sticky Note

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

3. Summary Table

Workflow	AI-powered student assistant for course information via Twilio SMS
Complexity	intermediate
Nodes	12
Categories	Support Chatbot, AI Chatbot
Author	Jimleuk
Published	09 Apr 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/3499/3499.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

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

Download workflow JSON Original n8n.io source Support Chatbot workflows AI Chatbot workflows

Frequently asked questions

What does AI-powered student assistant for course information via Twilio SMS do?

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.

Jimleuk

100 workflows

Nodes

n8n-nodes-base.twiliotrigger n8n-nodes-base.airtabletool n8n-nodes-base.set n8n-nodes-base.twilio n8n-nodes-base.airtable @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.memorybufferwindow

Complexity

intermediate

Published 09 Apr 2025

Likes 0

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Install path: /data/workflows/3499/3499.json

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AI-powered student assistant for course information via Twilio SMS

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS.

How it works

How to use

Requirements

Customising this workflow

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Twilio Trigger

Block 2 - Search Available Courses

Block 3 - Get Course Database Schema

Block 4 - Get User Message

Block 5 - Send SMS reply

Block 6 - Append to Call Log

Block 7 - Course Assistant Agent

Block 8 - Get List of Professors

Block 9 - Get List of Departments

Block 10 - Model

Block 11 - Memory

Block 12 - Sticky Note

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions