This n8n workflow is designed to efficiently manage and streamline SMS-based customer interactions via Twilio and Redis, while employing AI for intelligent responses. It buffers incoming messages, checks for message continuity, and consolidates multiple messages into a single AI-generated reply, enhancing conversation flow and user experience.

The workflow starts with the Twilio Trigger node listening for new inbound messages. Each message is then stored in a Redis list to create a message buffer associated with the sender’s phone number. After a brief pause of 5 seconds, the system compares the latest message with the previous one to determine if the user is sending a series of rapid messages or waiting for a reply.

If the system detects ongoing message activity, the process is repeated; otherwise, it proceeds to fetch the chat history and buffer the last messages. These messages are then sent to an AI agent powered by OpenAI through LangChain, which formulates a cohesive response based on the buffered conversation.

Finally, the AI response is sent back to the user via Twilio. The workflow is ideal for businesses that want to improve automated SMS customer service by handling message bursts gracefully and delivering more context-aware, consolidated replies. It’s particularly useful in scenarios involving support bots, lead capture, or any SMS-based conversational interface.

Node Count	11 – 20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.memoryManager, if, noOp, redis, set, stickyNote, twilio, twilioTrigger, wait