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Learn why most Retrieval-Augmented Generation (RAG) systems fail before the language model even processes queries and discover how open-source tools can create reliable enterprise-scale solutions. Explore the root causes of RAG failures, including broken document reading order, distorted tables, inconsistent formatting, and scattered metadata in enterprise PDFs that lead to irrelevant answers and hallucinations. Understand how Docling, an open-source document processing toolkit, converts complex PDFs, Word files, presentations, images, and audio into clean, structured content while preserving layout, hierarchy, tables, and multimodal elements. Discover OpenSearch as a fully open and scalable engine for vector indexing, hybrid retrieval, and metadata-driven search that complements document processing for robust RAG implementations. Examine overall architecture patterns, key design principles, and real-world implementation lessons learned from enterprise deployments. Follow along with a practical demonstration that processes a messy PDF through Docling, indexes it in OpenSearch, and queries it within a RAG workflow that consistently returns accurate context, providing a concrete roadmap for building reliable RAG applications using open-source technology.
