Turn raw content into searchable data with LangGraph.js and Redis Search
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.
Join to see a hands on demo and learn how to:
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
Speakers
Redis
Guy Royse
Sr. Developer Advocate
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