Building and querying knowledge graphs from unstructured sources.
Build a pipeline that turns YouTube podcasts into a knowledge graph: extract speakers, statements, and entities with an LLM, then dedupe them with embeddings.
Featuring production-ready resilience, structured error system, expanded integrations, and always-fresh structured context for agents operating in the real world.
Build a self-updating knowledge graph from meeting notes: extract decisions, tasks, owners, and relationships from your documents with CocoIndex and an LLM.
CocoIndex updates: in-process setup/drop API, the EmbedText building block, major SplitRecursively codebase-indexing improvements, union and NumPy type support, more LLM APIs, and the Kuzu graph target.
Build a real-time knowledge graph with Kuzu as a native CocoIndex target: incremental updates, high-performance graph queries.
Build a real-time product recommendation engine with an LLM and a graph database, from the aspect of product category (taxonomy) understanding.
CocoIndex updates: knowledge graph support, Qdrant and Supabase targets, KTable and LTable data types, additional LLM providers, and more.
CocoIndex now supports knowledge graphs with incremental processing. Building live knowledge for agents is super easy with CocoIndex!
CocoIndex is a data indexing platform for AI applications, handling ingestion, chunking, embedding, and pipeline management for RAG, semantic search, and knowledge graphs with built-in lineage and observability.