RAG
Retrieval-Augmented Generation combines internal data search with generative language models. I use it for knowledge bases, chatbots, and intelligent assistants that answer from verified sources.
A Knowledge Base for AI in Drupal: RAG and MCP in Practice
A Drupal knowledge base is where a company maintains, approves, and keeps its knowledge current. An AI assistant built on it answers from content somebody stands behind, rather than from a pile of documents. In Which Open-Source CMS Should You Choose for an AI Knowledge Base? I compare five systems. This article goes deeper into one of them: how to design a knowledge base in Drupal and connect it to AI through an API, RAG, and MCP.
Which Open-Source CMS Should You Choose for an AI Knowledge Base?
Most companies introducing an AI assistant over internal knowledge start with technology: which model, framework, or vector database to use. Those layers can be changed when needed. A knowledge base and CMS give an AI project a stable foundation: they determine where company knowledge is created, who maintains it, and how it stays current and approved. AI then works with information the company can trust. A CMS as a knowledge base, not only a website In an AI project, a CMS has a different role than on a website. It is where knowledge is created, structured, approved, and maintained, and where AI retrieves it. The selection criteria therefore differ: