Converting fixed-layout PDF files into editable Microsoft Word (`.docx`) documents requires reverse-engineering visual text positioning into flowing semantic structures. The engine analyzes character baselines, font weights, and line heights to reconstruct editable headings (H1–H3), standard paragraphs, and bulleted lists. Tabular data detection algorithms identify intersecting horizontal and vertical text alignments, synthesizing native Word table grids that can be formatted, edited, and computed in Microsoft Word, Google Docs, Apple Pages, and LibreOffice. Invaluable for updating legacy contracts where original Word source files have been lost, editing PDF resumes, and repurposing research papers.