RAG often looks economically attractive because it can improve answer quality while avoiding some training expense, but its real cost still depends on retrieval design, latency, and usage scale.
Glossary entry
RAG
Retrieval-Augmented Generation, an approach that combines a model with external information retrieval to improve relevance and grounding.
Why it matters
RAG matters because it can improve enterprise usefulness without full model retraining, but it also adds cost through retrieval pipelines, vector infrastructure, and orchestration.
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