RAG supplies information that model weights may not contain, such as internal policies, customer records, or recent documentation. The team can update the knowledge source without retraining or waiting for a new model.
Retrieved passages provide evidence that can be cited and inspected. Access filters can also limit which documents each user may see. These controls are difficult when facts exist only inside a model's weights.
Built-in knowledge is still useful for general language and reasoning. Use RAG when the answer depends on private, current, or source-specific facts. Evaluate retrieval carefully, since adding irrelevant documents can make the final answer worse.
Rewriting in plainer words…
This answer doesn't lend itself to a diagram - it reads best . No credits were charged.
