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What is RAG? Retrieval-Augmented Generation explained for BFSI practitioners

RAG (Retrieval-Augmented Generation) is a technique where an AI model fetches relevant documents or data from a private knowledge base before generating an answer. Think: LLM checks your bank's loan policies + customer file before drafting a credit decision, not hallucinating from generic training data.

WHY IT MATTERS

RAG is foundational for BFSI: enables models to cite source documents (auditable), stay current (no retraining), and respect data privacy (queries don't leave your infrastructure). Essential for compliance in lending, claims, and underwriting.

Source: AITechHive Learner Series

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What is RAG? Retrieval-Augmented Generation explained for BFSI practitioners — ath — AITechHive