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Introduction Hybrid Search for RAG combines keyword search and vector search to help AI applications retrieve more relevant information. Vector search is good at understanding meaning, while keyword search is useful when exact terms, names, product codes, or technical phrases matter. By using both approaches together, RAG systems can improve retrieval quality and provide LLMs... Continue Reading →
Introduction RAG architecture is emerging as a powerful approach to building reliable and accurate AI applications in today’s rapidly evolving digital landscape. As organisations increasingly adopt large language models (LLMs), one major challenge they face is ensuring that responses are factual, up-to-date, and contextually relevant. Traditional AI models rely only on their training data, which… Continue Reading →
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