We are thrilled to announce that SingleStore Kai, a MongoDB wire-compatible API, now offers integrated vector search capabilities, enabling 100x faster analytics and empowering gen AI use cases without code modifications, as the demand for intelligent AI applications surges with advancements in vector data utilization across various domains. With this update, Kai extends its powerful capabilities to include vector search, allowing developers to store and query vector data alongside operational data, combining features like full-text search and operational analytics within a single database without additional complexity. SingleStore provides multiple indexing options, including IVF_PQFS, which offers lower memory usage and faster index build times, outperforming competitors in recent benchmarks. To use vector search through SingleStore Kai, developers can create a collection with an embedding field, insert documents with embeddings, set up a vector index, and perform vector searches using MongoDB's familiar syntax. With enterprise capabilities and integrations like workload isolation and fast ingest of vector embeddings, SingleStore is a comprehensive solution suited for enterprises, supporting different MongoDB integrations and offering a free Starter workspace to explore these capabilities.