AI Jargon Buster
AI news and the language around it, simplified.
What is Retrieval Augmented Generation (RAG) (RAG)?
Retrieval Augmented Generation known as RAG is a method that connects an AI to your own private data sources. Normally, an AI relies only on the information it learned during its initial training. This can lead to outdated or generic answers. With this technique, the AI first searches your company files, internal wikis, or databases to find relevant facts. It then uses those specific facts to write a response. This process ensures the AI provides answers based on your current, verified information rather than relying on its memory alone. It acts like an open-book test where the AI is given the exact documents it needs to answer your question accurately.
Why this matters to you
This is the primary way businesses make AI reliable for daily work. It allows your team to use AI tools that understand your specific company policies, product manuals, or legal contracts. By grounding the AI in your own data, you significantly reduce the risk of the system making up facts. It turns a general-purpose tool into a specialized assistant that knows your business as well as you do.
How you might hear this
We are implementing a RAG system so our customer support team can query our entire archive of past tickets to find solutions for new issues instantly.
AI Jargon Buster
Search any AI term, explained in plain English.
Type a term below and search. You will be taken straight to the tool.
Related terms
See how your CV performs against the ATS algorithms that screen candidates before a human ever reads your application.
Try the CV Optimiser →How AI job displacement actually works, what it means for your career, and what to do about it. Written by someone who has been in recruitment for 25 years.
When the Ground Shifts →