Ragie, a retrieval-augmented generation (RAG) system, is evaluated against the LegalBench-RAG benchmark to assess its performance in handling legal texts, focusing on precision and recall. The benchmark involves four categories of legal documents: NDAs, private contracts, M&A documents, and privacy policies. Ragie demonstrates superior performance in precision and recall compared to industry standards, particularly when employing hybrid retrieval, reranking, and hierarchical retrieval methods. With recall accuracy reaching up to 99.4%, Ragie effectively retrieves relevant information, making it a reliable system for complex queries. The system's flexibility allows developers to optimize between precision and recall based on specific needs, with reranking enhancing precision and hierarchical retrieval further improving accuracy. These results affirm Ragie's capability for production use in legal and other domain-specific applications, with an example of an immigration law firm achieving a tenfold increase in legal drafting speed using Ragie's system.