General purpose language models do not know your internal procedures. RAG architecture makes the model retrieve relevant passages from your own document pool before generating an answer, so responses are both current and grounded in a source.
What to watch when building RAG
- Document chunking strategy directly affects answer quality
- Access rights must be enforced at the retrieval layer
- The source of an answer should be shown to the user
- Outdated documents must be pruned regularly
- Improvement cannot be measured without an evaluation set
A well-designed RAG system lets you keep your knowledge layer even when you change the underlying model.