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RAG Solved the Wrong Problem: What Actually Makes AI Applications Reliable?

Your team ships an internal AI assistant grounded on company documents. The demo is excellent: ask about the refund policy, and the model answers with confident prose. Then production happens.

  • RAG provides relevant context but doesn't solve reliability issues.
  • Reliability requires current, authorized, audit-ready, and safe information.
  • Building reliable AI needs multi-faceted approach beyond data feeding.

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