Date: 04/09/2025
Okay, this video looks like gold for where I’m trying to go with my workflow! It’s all about building a local AI agent using n8n for automation, Ollama for the LLM, and PostgreSQL for vector storage. The beauty is that it’s entirely self-hosted, which means no hefty API bills or privacy concerns. The video walks you through the entire process, from setting up Ollama and PostgreSQL to orchestrating everything within n8n. They even tackle common troubleshooting issues.
This is exactly the kind of thing I need to dive deeper into. For the past year, I have been looking at self-hosted AI for cost reasons and privacy, but found it daunting to integrate it into actual workflows. Right now, I still use OpenAI for all my jobs, but it would be great to use this at least for local testing or for clients who have compliance issues. It seems possible I could create a RAG workflow that does not leave the customer premises. Imagine automating report generation, content summarization, or even personalized customer service bots, all running locally!
The video shows how to add RAG (Retrieval Augmented Generation) and tools into the workflow, which opens up huge possibilities for automating complex tasks. It’s worth experimenting with because it gives you a practical, hands-on approach to building AI solutions without being locked into external services. I’m always looking for ways to streamline development and cut costs, and this seems like a very promising avenue to explore.