🚀 Built an Advanced AI Customer Support Automation with n8n I’ve completed AI Customer Support v2, a significantly more advanced version of my previous customer support workflow. The workflow now includes: • 79 nodes and 72 connections • Multi-channel intake: Web, WhatsApp, Telegram, Email, and Discord • Rate limiting and customer resolution • Conversation and escalation management • RAG-based knowledge retrieval • Sentiment analysis • Intent classification • Multi-agent routing with 5 specialized AI agents • AI tool calling for orders, refunds, email, and password reset • Automated human handoff and ticket creation • Analytics and AI execution logging • SLA monitoring and health checks • Scheduled background processes The architecture is divided into several layers: Intake → Intelligence → Tool Calling → Response → Observability I also designed the workflow with customization in mind, including the ability to add new AI specialists, tools, and LLM providers. This project was built to explore how n8n can be used beyond simple AI workflows and into more structured, production-oriented automation systems. There are still areas I want to improve, particularly vector-based RAG, native function calling, and scaling the LLM layer. Next step: documenting and publishing the project on GitHub. Tagar#n8n Tagar#AIAutomation Tagar#AIEngineering Tagar#Automation Tagar#AIAgent Tagar#CustomerSupport Tagar#RAG Tagar#WorkflowAutomation