RAG Architectures AI Builders Should Understand
Retrieval-augmented generation (RAG) addresses a critical gap in AI systems by creating an evidence-based pathway that keeps responses current, respects privacy boundaries, and provides verifiable sources rather than relying on potentially outdated training data. RAG works by first retrieving relevant evidence from databases or documents, then constraining the AI's response to cite only that retrieved information,...