Raw text from articles, documents, and emails has no value until it's searchable. AI-powered ingestion pipelines built with LangGraph.js take unstructured content and transform it into structured, vectorized data, stored in Redis and instantly queryable, both lexically and semantically, with Redis Search.

• Build a multi-node LangGraph.js workflow that summarizes, classifies, extracts entities, and creates vector embeddings from raw text
• Store structured and vector embeddings in Redis as JSON documents
• Combine structured filters and semantic similarity in a single query with Redis Search