In this talk, we examine the state-of-the-art in AI-powered search and retrieval. We detail techniques for enhancing performance beyond base embedding models, including hybrid search, reranking strategies, query decomposition and document enrichment, the use of domain-specific and fine-tuned embeddings, custom data processing pipelines (ETL), and contextualized chunking methods.