The Timescale Vector integration for LangChain enables developers to build better AI applications with PostgreSQL as their vector database, offering faster similarity search, efficient time-based search filtering, and operational simplicity of a single cloud PostgreSQL database. This integration enhances pgvector with state-of-the-art ANN index inspired by the DiskANN algorithm, achieving 243% faster search speed at ~99 % recall than Weaviate and outperforming all existing PostgreSQL search indexes. Timescale Vector also supports time-based context retrieval for RAG and advanced self-querying capabilities in LangChain applications.