CocoIndex is a framework designed to streamline incremental data flows that integrate both structured and unstructured data sources, particularly using PostgreSQL. It allows for uniform handling of data operations, including AI transformations like generating embeddings, while ensuring operational simplicity and data consistency. The example provided demonstrates how to read, transform, and store product data efficiently for semantic search capabilities.

Build and deploy AI agent workflows quickly using Sim, a cloud-hosted service that requires Docker and PostgreSQL with the pgvector extension. The article details the installation process, including commands for setting up the application and running it with local AI models. It also covers the necessary configurations for development environments and offers options for using PostgreSQL.