Building Production-Grade RAG: From Prototype to Enterprise Scale
Published by: Altimet AI Engineering Team
"Moving Retrieval-Augmented Generation from a basic demo to a production-ready enterprise search system requires overcoming hurdles. Learn how to optimize chunking and reranking."
Building a vector search demo is simple, but scaling it for enterprise use is a challenge. Issues like poor text parsing, context window limitations, and lack of metadata control can lead to unreliable results. To build a robust system, focus on three areas: 1. Document Ingestion: Clean and structure PDFs, tables, and images. 2. Chunking Strategies: Use hierarchical chunking to maintain document context. 3. Reranking: Apply a hybrid search approach, combining lexical and semantic search with cross-encoder reranking to ensure the most relevant results are returned.
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