n8n Launches No-Setup RAG Template with Vector Store and OpenAI

n8n is rolling out a Retrieval-Augmented Generation (RAG) starter template designed to help users build document-based chatbots with minimal effort. The template includes two workflows—one for ingesting knowledge and the other for querying it—leveraging the Form Trigger node, Simple Vector Store, and OpenAI API. Users can upload any document, which is then split, embedded, and stored for immediate chatbot interaction.

This release simplifies what has traditionally been a complex pipeline involving embeddings, storage infrastructure, and front-end interfaces. n8n handles the entire flow in a no-code environment. Users can customize prompt logic, swap out vector store implementations, or extend the ranking system with minimal changes.

The template is aimed at automation builders, no-code developers, and internal knowledge teams who want to test RAG capabilities without engineering overhead. It positions n8n as a viable rapid-prototyping tool for AI-driven workflows, competing with more technical platforms like LangChain and Haystack.