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Enhance customer chat by buffering messages with Twilio and Redis

JimleukJimleuk
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2/3/2026
Google SheetsZoho CRMAutomationData SyncLeads
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This n8n workflow demonstrates a simple approach to improve chat UX by staggering an AI Agent's reply for users who send in a sequence of partial messages and in short bursts.

How it works

  • Twilio webhook receives user's messages which are recorded in a message stack powered by Redis.
  • The execution is immediately paused for 5 seconds and then another check is done against the message stack for the latest message.
  • The purpose of this check lets use know if the user is sending more messages or if they are waiting for a reply.
  • The execution is aborted if the latest message on the stack differs from the incoming message and continues if they are the same.
  • For the latter, the agent receives the buffered messages up to that point and is able to respond to them in a single reply.

Requirements

  • A Twilio account and SMS-enabled phone number to receive messages.
  • Redis instance for the messages stack.
  • OpenAI account for the language model.

Customising the workflow

This workflow should work for other common messaging platforms such as Whatsapp and Telegram.

5 seconds too long or too short? Adjust the wait threshold to suit your customers.

Enhance Customer Chat by Buffering Messages with Twilio and Redis

This n8n workflow enhances customer chat interactions by buffering messages using Redis and intelligently responding via Twilio, optionally with an AI Agent. It provides a robust solution for managing incoming Twilio SMS messages, allowing for delayed or AI-powered responses.

What it does

This workflow automates the following steps:

  1. Listens for Incoming Twilio SMS: The workflow is triggered by an incoming SMS message to a configured Twilio number.
  2. Buffers Messages in Redis: It stores the incoming message, sender, and recipient in a Redis database. This acts as a buffer, allowing the system to hold messages before deciding on an action.
  3. Conditional Logic for Response:
    • If AI is Enabled: If the AI_ENABLED environment variable is set to true, the workflow proceeds to process the message with an AI Agent.
      • Manages Chat Memory: It uses a Chat Memory Manager with a Simple Memory buffer to maintain conversational context.
      • Processes with OpenAI Chat Model: An OpenAI Chat Model is used by the AI Agent to generate a response based on the incoming message and conversation history.
      • Sends AI Response via Twilio: The AI-generated response is sent back to the customer via Twilio.
    • If AI is Disabled: If AI_ENABLED is false, the workflow does nothing, effectively buffering the message without an immediate automated response. This branch includes a "No Operation" node and a "Sticky Note" indicating that AI is disabled.
  4. Optional Delay: A Wait node is included, which can be configured to introduce a delay before processing or responding to messages. (Note: In the provided JSON, this node is not connected, but its presence suggests an intended use for delaying actions.)

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Twilio Account: A Twilio account with a phone number capable of sending and receiving SMS.
    • Twilio Credentials: Configure Twilio credentials in n8n.
  • Redis Instance: Access to a Redis database.
    • Redis Credentials: Configure Redis credentials in n8n.
  • OpenAI Account (Optional): If you intend to use the AI Agent for responses.
    • OpenAI API Key: Configure OpenAI credentials in n8n.
  • Environment Variables:
    • AI_ENABLED: Set to true to enable AI responses, or false to disable.

Setup/Usage

  1. Import the Workflow:
    • Download the provided JSON and import it into your n8n instance.
  2. Configure Credentials:
    • Update the "Twilio Trigger" node with your Twilio credentials.
    • Update the "Redis" node with your Redis credentials.
    • If using AI, update the "OpenAI Chat Model" node with your OpenAI credentials.
    • Update the "Twilio" node (for sending responses) with your Twilio credentials.
  3. Set Environment Variables:
    • Ensure the AI_ENABLED environment variable is correctly set in your n8n environment or directly within the "If" node's expression if preferred.
  4. Activate the Workflow:
    • Enable the workflow in n8n.
  5. Configure Twilio Webhook:
    • In your Twilio account, configure the webhook URL for your Twilio phone number to point to the webhook URL provided by the "Twilio Trigger" node in n8n. This will ensure incoming messages trigger the workflow.

Once configured, any SMS sent to your Twilio number will be processed by this workflow, buffered in Redis, and optionally responded to by the AI Agent.

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