Quick overview
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. Setup Configure AiSensy to send message events to this workflow’s webhook URL (path: /whatsapp-support). Add a Groq API credential in n8n and select it in the Groq LLM node. Create a Google Sheets FAQ knowledge base with question and answer columns, connect Google Sheets credentials, and select the document and sheet in the “Load Knowledge Base” step. Create a Google Sheets conversation log sheet, connect it in the “Log to Sheets” step, and ensure it has columns for timestamp/phone/name/message/intent/urgency/language/reply. Replace YOUR_AISENSY_API_KEY, confirm the support-reply template exists in AiSensy with one parameter, and set any campaign/template values as needed. Add Gmail OAuth credentials and set the complaint notification recipient email, and add Telegram bot credentials and replace YOUR_TELEGRAM_CHAT_ID for escalation alerts. An n8n automation workflow template by Utkarsh Kapoor.
Utkarsh Kapoor
web
free
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