Engineering Production-Ready RAG: Mastering Semantic Chunking for Enterprise Knowledge Systems

RAG systems are critical for enterprises augmenting language models with proprietary knowledge without retraining. This article reveals that semantic chunking of Chinese text can improve retrieval accuracy by 23%—a crucial optimization often overlooked in production deployments. For developers building enterprise Q&A systems, mastering chunking strategies, embedding model selection, and proper evaluation methods is essential for deploying reliable and traceable AI systems.