The text introduces a method for enhancing search quality by integrating semantic search technology using the Rerank endpoint, which can be incorporated into a user's existing search stack with a single line of code. It describes how Rerank can improve search results for over 100 languages by computing relevance scores to reorder search results, making it highly effective when combined with a first-stage retrieval system that filters top documents. The text provides a practical example using Elasticsearch to demonstrate the process and highlights the significant improvements in search accuracy when Rerank is applied. Evaluation results indicate that Rerank outperforms traditional lexical and embedding-based semantic searches by providing more relevant results in the top three positions for a larger percentage of queries. The Rerank tool is portrayed as an augmentative rather than a replacement solution, offering simplicity and performance improvements for existing search systems and encouraging users to provide feedback for further enhancements.