Multi-Agent Systems Design: AI Customer Support with n8n

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The challenge for most enterprises is not awareness of AI. It is the gap between knowing what AI can do and having teams who can build and deploy it. This course closes that gap by allowing you to design and deploy a 4-agent AI customer support pipeline using n8n, MCP, and RAG. Here is what you will mainly build: Multi-Agent Pipeline Design: Configure a system where a Classifier Agent triages queries, a Reply Builder generates responses, & a Human-in-the-Loop layer gives your team control over every interaction. RAG-Powered Knowledge Base: Connect a Supabase knowledge base via. MCP so, each of the AI response is grounded in actual support content. AI Classification & Automated Replies: Build a GPT-4o-mini-powered classifier that typically reads emails, scores confidence, and routes tickets with a Telegram approval step for flagged cases. Testing and Production Deployment: Validate the pipeline with real data and deploy to a live environment so the system runs without manual intervention. Designed for enterprise teams and professionals ready to move from AI strategy to AI execution. 160+ LearnKartS courses have put 200,000+ learners ahead of the curve. Build your first production AI system today.

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Nikhil Agarwal

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LearnKartS

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