This session will delve into the critical factors that directly influence semantic search accuracy within AI applications, particularly for Retrieval-Augmented Generation (RAG) systems. We will explore how the choice and configuration of a vector database fundamentally impact the quality of initial retrievals, and then demonstrate how reranker play a crucial role in further optimizing these results. Attendees will learn actionable strategies to fine-tune their semantic search pipelines, ensuring their AI and RAG implementations deliver highly relevant and factual information.