💬 Enhance customer chat by buffering messages with Twilio and Redis
⚡ 10,785 views · 💬 Support Chatbots
Description
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.
🔗 Nodes Used
Redis, Twilio, AI Agent, OpenAI Chat Model, Simple Memory, Chat Memory Manager
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File