This example demonstrates Datalab’s ability to extract mathematical PDFs containing dense notation, equations, and references — a task where standard OCR systems often fail.

Blocks View

Shows structured document elements derived from Datalab’s JSON output, with citations linking each block to its precise source location. This makes every extracted formula or paragraph traceable and usable for downstream workflows like dataset creation or fine-grained search.

Markdown Output (with LaTeX)

Converts equations and inline expressions into clean, typeset LaTeX, preserving structure and readability for technical review or reuse in research tools.

Parsing math-heavy PDFs is a complex problem: equations are not simply text — they blend symbolic, spatial, and typographic cues. Standard OCR systems often flatten them or break logical groupings.

By combining accurate LaTeX reconstruction with citation-backed structure, Datalab turns complex mathematical documents into high-fidelity, machine-readable data — ready for reproducible research, analysis, and AI training.