Palak Agarwal and Omar Alhait demonstrate how document parsingIntelligent document processing uses AI to classify, extract and validate information from documents for downstream workflows. supports searchable applications. Handwritten flight logs, complicated layouts and inconsistent PDFs illustrate why extraction must preserve reading order and structure before downstream software can use the results. The account describes the engineering workflow without reproducing private personal information or allegations from the source documents.
The workshop moves from parsing to structured schemas and an API pipelineAn application programming interface is a defined way for software systems to request data or actions from one another.. A resume example contrasts quick schema generation with a schema informed by parsed document content, while questions explore nested fields, figures, citations and a hybrid use of OCR and PDF metadata. Alhait explains the risk of visual-only redaction and describes preserving material intended to remain hidden.
The evaluation discussionEvaluation measures how well an AI system performs against defined tasks, criteria and failure conditions using repeatable evidence. recommends inspecting small samples and building representative benchmarksA benchmark is a standardized task or collection of tests used to compare AI systems under defined conditions. before scaling. Document-specific configurations and labelled examples help identify errors that broad accuracy claims can hide. Fundraising, customer superlatives, hiring, signup and giveaway appeals are omitted.
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