Automating WhatsApp Replies Using GoHighLevel with Redis and Anthropic

# Automating WhatsApp replies in Go High Level with Redis and Anthropic ## Description Integrates GHL + Wazzap with Redis and an AI Agent using ClientInfo to process messages, generate accurate replies, and send them via a custom field trigger. --- ## Who's it for This workflow is for businesses using **GoHighLevel (GHL)**, including the **Wazzap** plugin for WhatsApp, who want to automate inbound SMS/WhatsApp replies with AI. It's ideal for teams that need accurate, data-driven responses from a predefined **ClientInfo** source and want to send them back to customers without paying for extra inbound automations. --- ## How it works / What it does 1. **Receive message** in n8n via Webhook from GHL (**Customer Replied (SMS)** automation). WhatsApp messages arrive the same way using the **Wazzap** plugin. 2. **Filter message type**: * If audio — skip processing and send fallback asking for text. * If text — sanitize by fixing escaped quotes, escaping line breaks/carriage returns/tabs, and removing invalid fields. 3. **Buffer messages** in Redis to group multiple messages sent in a short window. 4. **Run AI Agent** using the **ClientInfo** tool to answer only with accurate service/branch data. 5. **Sanitize AI output** before sending back. 6. **Update GHL contact** custom field (**IA_answer**) with the AI's response. 7. **Send SMS reply** automatically via GHL's outbound automation triggered by the updated custom field. --- ## How to set up 1. In **GHL**, create: * **Inbound automation**: Trigger on *Customer Replied (SMS)* — Send to your n8n Webhook. * **Outbound automation**: Trigger when **IA_answer** is updated — Send SMS to the contact. * Create a custom field named **IA_answer**. 2. Connect **Wazzap** in GHL to handle WhatsApp messages. 3. Configure **Redis** in n8n (host, port, DB index, password). 4. Add your **AI model** credentials (Anthropic, OpenAI, etc.) in n8n. 5. (Optional) Set up the **Google Drive Excel Merge** sub-workflow to enrich ClientInfo with external data. --- ## Requirements * **GoHighLevel sub-account API key**. * **Anthropic (Claude)** API key or another supported LLM provider. * **Redis database** for temporary message storage. * **GHL automations**: one for inbound messages to n8n, one for outbound replies when **IA_answer** is updated. * **GHL custom field**: **IA_answer** to store and trigger replies. * **Wazzap plugin** in GHL for WhatsApp message handling. --- ## How to customize the workflow * Add more context or business-specific data to the **AI Agent prompt** so replies match your brand tone and policies. * Expand the **ClientInfo** dataset with additional services, branches, or product details. * Adjust the **Redis wait time** to control how long the workflow buffers messages before replying.