Builds real-time data transformation pipelines and vector search indexes for AI applications.
CocoIndex is an ultra-performant real-time data transformation framework for AI applications. This skill enables developers to build complex indexing flows that extract data from sources like S3 or local files, apply AI-driven transformations such as chunking and embedding, and export results to vector or graph databases. With built-in support for incremental processing and live updates, it streamlines the creation of production-grade RAG pipelines and knowledge extraction workflows.
Key Features
01Seamless integration with Qdrant, Neo4j, pgvector, and LanceDB
02Incremental processing to sync only changed data efficiently
03Built-in support for text chunking and LLM-based extraction
04Automated type inference for streamlined schema management
05Real-time ETL pipelines for embeddings and knowledge graphs
0637 GitHub stars
Use Cases
01Creating a live-updated vector search index for enterprise documentation
02Implementing efficient data pipelines from S3 to vector databases
03Building automated knowledge graphs from unstructured text using LLMs
