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Invention: The present invention relates to a system and method for transforming non–machine-readable or poorly structured digital documents, particularly Portable Document Format (PDF) files, into an optimized Agent Document Format (ADF) designed for efficient processing by artificial intelligence agents. Many traditional PDFs contain complex layouts, embedded images, scanned text, and inconsistent formatting that hinder automated interpretation and extraction by AI systems. The invention introduces a conversion pipeline that parses document structures, extracts semantic content, and reorganizes the information into a standardized, lightweight, and structured representation that is directly consumable by AI agents and automated workflows. By normalizing textual content, removing redundant visual formatting, and structuring the document into hierarchical machine-readable components, the system significantly reduces computational overhead and token consumption during AI processing while improving accuracy and speed of document analysis. The resulting ADF enables AI agents to perform tasks such as information retrieval, summarization, reasoning, and data extraction more efficiently within agentic architectures where large language models interact with tools and external data sources to accomplish tasks. The invention therefore provides a scalable framework for converting legacy and complex document formats into AI-optimized data structures, enabling faster processing, lower operational cost, and improved interoperability across AI-driven applications, document management systems, and automated knowledge workflows.