Turn Your WordPress Site into a RAG Knowledge Base
AI is changing how users interact with websites, but generic AI models often lack knowledge of your site’s unique content and can produce inaccurate or outdated responses. Retrieval-Augmented Generation (RAG) solves this problem by combining the power of large language models with your own WordPress content.
In this session, you’ll learn how to turn a WordPress website into a reliable AI knowledge base. We’ll walk through the complete RAG pipeline—from extracting content using the WordPress REST API or sitemaps, to cleaning and chunking content, generating embeddings, storing them in a vector database, and retrieving the most relevant information to produce accurate, source-backed responses.
We’ll also explore practical implementation choices for PHP and WordPress developers, including vector databases along with best practices for keeping your knowledge base synchronized as your content changes.
To bring everything together, the session will include a live demonstration of an AI assistant answering questions using only the content from a WordPress site, complete with links back to the original pages.
Whether you build client websites, manage documentation, run an online store, or maintain a content-rich website, you’ll leave with a clear understanding of how to integrate AI into WordPress in a practical, trustworthy, and scalable way.
Key takeaways
- Understand what Retrieval-Augmented Generation (RAG) is and why it’s more reliable than using a standalone LLM for website content.
- Identify the WordPress content sources (posts, pages, custom post types, WooCommerce products, etc.) that can be used to build a knowledge base.
- Understand the complete RAG workflow—from content extraction and chunking to embeddings, vector databases, retrieval, and AI-powered responses.
- Gain practical insights through a live demonstration of building an AI assistant powered by a WordPress website.
- Leave with a clear roadmap to implement RAG in their own WordPress projects.