Retrieval-Augmented Generation (RAG)
An AI pattern that retrieves external data before generating an answer.
What is Retrieval-Augmented Generation (RAG)?
Retrieval-Augmented Generation (RAG) is part of the basics vocabulary. In practice, it describes an AI pattern that retrieves external data before generating an answer. The exact implementation varies by platform, but the useful meaning stays the same: it helps teams name a specific part of how products, content, AI answers, or commerce operations work.
Why it matters
Retrieval-Augmented Generation (RAG) matters because AI commerce still depends on basic retail operations. If catalog, inventory, checkout, or fulfillment data is unclear, AI systems and shoppers both struggle to trust the result.
How Ranketta uses this concept
Ranketta uses this ecommerce foundation when it audits product feeds and connects AI visibility back to real catalog, SKU, vendor, and checkout data.