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Where to Use Training, Where to Use RAGs?

Recent advancements in large language models LLMs have created a critical decision point for enterprises: whether to invest in model training (fine-tuning) or adopt Retrieval-Augmented Generation RAG systems. This distinction is not merely academic-misunderstanding these concepts can lead to misallocated resources, with potential financial implications exceeding hundreds of thousands of dollars per contract. While C-level executives often conflate "training" with "retrieving," the technical and operational differences between these approaches demand careful analysis. This report synthesizes insights from industry practices, cost analyses, and technical benchmarks to provide decision-makers with a framework for optimizing LLM deployments.