WhatsApp Message Handling and AI Automation Workflow

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This n8n workflow automates the processing of WhatsApp messages, enabling intelligent responses and notifications through AI integration. Designed for customer support or inquiry management, it listens for incoming WhatsApp submissions via a webhook trigger. Once a message is received, it is evaluated to determine if it is text-based. If so, the message is processed using an OpenAI language model for potential AI-driven responses. Memory buffers are used to retain context, allowing for coherent conversations. If the message is not text, a fallback response is sent. The workflow also includes nodes for drafting and sending email notifications through Gmail, ensuring users are kept informed about interactions. Additionally, it uses sticky notes for internal documentation or annotations and has dedicated nodes for sending replies on WhatsApp. Overall, this workflow streamlines the interaction between users via WhatsApp, AI-powered processing, and email notifications, making it ideal for support bots, inquiry handling, or automated communication systems.

Node Count

>20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, gmail, if, noOp, set, stickyNote, whatsApp, whatsAppTrigger

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