Date: 09/22/2025
Okay, this n8n RAG scaling video is straight fire for anyone diving into AI-powered workflows! It tackles a real-world problem I’ve definitely hit: building a killer RAG system is easy with a few files, but what happens when you need to ingest thousands? This video shows you how to use n8n, Supabase, and some clever orchestrator patterns to reliably process massive amounts of data. We’re talking scaling to thousands of files per hour.
What makes this valuable is its focus on practical solutions to common AI integration bottlenecks. API rate limits, memory overloads, system instability – these are the dragons you face when moving from a PoC to a production-ready system. The video breaks down how to build an orchestrator workflow that handles parallel executions, tracks parent/child processes using Supabase, and even handles errors with automated retries. Plus, the deep dive into using webhooks instead of sub-workflows is a game-changer for performance and tracking – something I’ve been experimenting with myself lately and seen HUGE improvements from.
Imagine building a document processing pipeline for a legal firm or a content ingestion system for a large e-commerce site. This video provides a blueprint for automating those processes at scale. Honestly, the techniques for handling errors and preventing system overloads are worth the price of admission alone. I’m definitely going to be experimenting with these orchestration patterns in my next project. The layered error handling and Supabase configuration tips are gold!