The Document Parsing Bottleneck: Multimodal AST Layout Engines, Table Reconstruction, and Deterministic Retrieval in High-Consequence Enterprise RAG

Abstract

Enterprise Retrieval-Augmented Generation (RAG) deployments in mission-critical environments—such as statutory compliance, corporate finance, aerospace maintenance, clinical trials, and commercial liability adjudication—consistently fail not at the generation layer, but at the ingestion interface. Standard document ingestion architectures rely on naive text extractors or heuristic OCR pipelines that linearize two-dimensional page geometries into one-dimensional character sequences. This operational abstraction discards essential topological structures: coordinate-bounded tables, multi-tier heading hierarchies, spanning column groupings, and footnote associations.

In this dissertation, we examine the physics of document ingestion failure across complex corporate documents.…