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RAG (Retrieval-Augmented Generation): connecting LLMs to your data

RAG is a technique that lets language models pull real-time information from databases or documents before answering a question. Instead of relying only on training data, the model retrieves fresh, specific info and uses it in its response. Think: AI customer-service agent querying your bank's account policies live.

WHY IT MATTERS

RAG is the workhorse pattern for enterprise AI in banking—credit-risk models, compliance Q&A, KYC workflows all use it to ground AI outputs in current, auditable sources.

Source: AITechHive · 2026-08-30

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RAG (Retrieval-Augmented Generation): connecting LLMs to your data — ath — AITechHive