Loop Engineering with Adaptive PDF Parsing: Start Cheap, Pay for a Heavier Parser Only When the Page Needs It

Processing documents for AI systems creates a difficult trade-off, as fast parsers fail on complex tables while powerful ones are too expensive to use on every page. Adaptive parsing solves this by first running a cheap, baseline parser across the entire document. A cascade of automatic checks then evaluates the output on each page, flagging potential failures like flattened tables or missing figures. Only the pages that fail these checks are escalated to a more powerful and costly parser, ensuring expensive resources are applied surgically where they are truly needed. This "start cheap, escalate when necessary" approach dramatically reduces cost and processing time without sacrificing accuracy.