Retrieval-Augmented Generation (RAG) for Websites

RAG is the mechanism through which your website content directly powers AI-generated answers.

Retrieval-Augmented Generation (RAG) combines LLM generative capabilities with real-time information retrieval. When a user submits a query, the system first retrieves relevant documents from the web, then uses these as context to generate an accurate, grounded response. This is the technology enabling Perplexity, Google's AI Overviews, and ChatGPT browsing to provide current, cited answers.

Optimizing Your Website for RAG Systems

Ensure crawler accessibility — check your robots.txt to confirm GPTBot, PerplexityBot, and other AI crawlers are not blocked. Create semantically rich content that covers topics from multiple angles. Maintain content freshness through regular updates. Organize content into clear, self-contained sections that enable passage-level retrieval.

RAG Optimization for Wix Websites

FLOR-IT implements RAG-optimized content strategies for Wix businesses — from technical crawler accessibility to semantic content depth to passage-level structure. Every dimension of the RAG pipeline is addressed to maximize your citation frequency in AI-generated answers.