What is RAG (Retrieval-Augmented Generation)?

RAG combines information retrieval with AI text generation, allowing AI systems to access external documents and provide more accurate, sourced responses.

RAG addresses a key limitation of large language models: they can only draw on knowledge from their training data. By adding a retrieval step, RAG systems search for relevant documents in real-time and use that information to generate responses. This enables AI to access current information, cite sources, and reduce hallucinations.

Why it matters

RAG matters because it's becoming the standard for AI systems that provide factual, current information. As more AI tools adopt RAG architectures, being a quality source that gets retrieved and cited becomes increasingly valuable. For brands, RAG-based systems offer transparency into AI visibility. You can see citations, understand what content gets retrieved, and optimize accordingly. This makes AI visibility more actionable than with opaque base model recommendations.

What people get wrong

• RAG means AI always gives accurate answers. RAG reduces but doesn't eliminate errors. Poor sources can lead to poor answers, and AI can still misinterpret retrieved content.
• RAG is just AI with search. RAG involves sophisticated retrieval, ranking, and context integration. It's more complex than simply adding search to AI.
• All AI systems use RAG. Many AI interactions use base models without retrieval. RAG is an enhancement, not a universal feature.

Related terms

Perplexity: Perplexity is a leading AI search engine built on RAG architecture.

Hallucination: RAG helps reduce hallucinations by grounding responses in real documents.

AI Citation: RAG enables AI to cite specific sources, creating citation visibility opportunities.

LLM: RAG augments LLM capabilities by adding retrieval before generation.

Track visibility in RAG-based AI systems

Trakkr monitors your citation visibility in RAG-powered platforms like Perplexity. See when your content is retrieved and cited, and understand which content earns AI citations.