🤖 Automating WhatsApp replies using Go High Level with Redis and Anthropic
⚡ 949 views · 🤖 AI Chatbots & Agents
Description
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
- Receive message in n8n via Webhook from GHL (Customer Replied (SMS) automation). WhatsApp messages arrive the same way using the Wazzap plugin.
- 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.
- Buffer messages in Redis to group multiple messages sent in a short window.
- Run AI Agent using the ClientInfo tool to answer only with accurate service/branch data.
- Sanitize AI output before sending back.
- Update GHL contact custom field (IA_answer) with the AI’s response.
- Send SMS reply automatically via GHL’s outbound automation triggered by the updated custom field.
How to set up
- 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.
- Connect Wazzap in GHL to handle WhatsApp messages.
- Configure Redis in n8n (host, port, DB index, password).
- Add your AI model credentials (Anthropic, OpenAI, etc.) in n8n.
- (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.
🔗 Nodes Used
HTTP Request, Redis, Webhook, Google Drive, Execute Workflow Trigger, AI Agent
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File