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What is RAG? How retrieval-augmented generation grounds AI in real data

RAG (retrieval-augmented generation) is a technique that lets AI models fetch up-to-date documents, databases, or knowledge sources *before* answering a question. Instead of relying only on training-data memory, RAG pulls fresh facts in real-time, reducing hallucinations and keeping answers current.

WHY IT MATTERS

RAG is foundational for BFSI AI: regulatory documents, customer records, transaction history, and compliance rules must be live and accurate. Paywhere's banking channel (above) likely uses RAG to fetch account data on demand without retraining the model.

Source: AITechHive · 2026-09-23

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What is RAG? How retrieval-augmented generation grounds AI in real data — ath — AITechHive