Astra DB Hybrid Search is an enhanced search feature that combines vector search and lexical search to improve retrieval accuracy in production AI systems, including those powered by generative AI. The new feature uses the NVIDIA NeMo Retriever reranking microservices to reorder top results based on fine-tuned LLM models, significantly improving relevance. By leveraging Astra DB's hybrid search approach, developers can achieve up to 45% improvement in search relevance and ensure that their GenAI applications return accurate responses. The feature is available on Langflow and in the Data API in April, and users can sign up for a webinar to learn more about its capabilities.