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Your RAG (retrieval augmented generation) system is a nightmare of duct tape and broken promises—it probably involves chunking strategies you copied-and-pasted from Stack Overflow (and ChatGPT), embedding models you selected at random (evals who?), and retrieval that breaks whenever someone adds a new PDF.AutoRAG simplifies the RAG process, eliminating that entire mess by providing a fully-managed RAG pipeline that automatically handles ingestion, chunking, embedding, and retrieval. We'll build a production-ready knowledge system that continuously monitors your data sources and keeps your AI fresh without you having to lift a finger. Live demo includes feeding AutoRAG corporate PDFs, transcripts, and scraped web pages and watching it automatically transform chaos into intelligent search.
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