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Cutting RAG inference costs 6x starts with deciding what never reaches the LLM
Most teams building retrieval augmented generation (RAG) systems for high stakes classification make the same architectural bet: Route ev…
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Most teams building retrieval augmented generation (RAG) systems for high stakes classification make the same architectural bet: Route every ambiguous case straight to the language model and trust the retrieved context to sort it out. This works fine in a demo.
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