Quick overview This workflow receives incoming WhatsApp messages via an n8n webhook, loads an FAQ knowledge base from Google Sheets, and uses Groq (Llama 3.3) to classify intent and generate a reply. It sends the response through the AiSensy API, logs the conversation to Google Sheets, and alerts via Gmail and Telegram. How it works Receives a POST request from AiSensy on a WhatsApp webhook when a customer sends a message. Extracts the customer phone, name, message text, and timestamp, and ignores requests missing required fields. Loads FAQ question-and-answer rows from Google Sheets and sends them with the customer message to Groq (Llama 3.3) to classify intent, detect language and urgency, and draft a reply. Parses and validates the model’s JSON output and formats a safe fallback reply if parsing fails. Sends the generated reply back to the customer using the AiSensy WhatsApp API. Sends a Gmail alert when the intent is COMPLAINT and posts a Telegram alert when the intent is ESCALATE. Appends or updates a conversation log row in Google Sheets and returns a 200 OK webhook response.
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Gmail
Google Sheets
Groq Chat ModelWHTTP RequestRelated workflows
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