Why GroundX wins
What OCR sees vs. what GroundX understands
Most extraction tools treat documents as flat text. GroundX treats them as visual objects — preserving the relationship between labels and values, table cells and their context, page sections and their meaning.
Spatial layout
OCR flattens to a stream of characters, losing the two-dimensional structure of the page.
GroundX preserves x/y position, column alignment, and label–value proximity.
Table structure
OCR reads rows as separate strings with no awareness of which column a value belongs to.
GroundX reconstructs cell relationships, column headers, and spanning cells.
Cross-page context
OCR treats each page independently — tables that span pages, or totals that reference prior rows, are lost.
GroundX maintains context across page boundaries.
Visual ambiguity
Handwriting, stamps, watermarks, and rotated text cause OCR to produce garbled or missing output.
GroundX's visual understanding handles non-standard layouts and handwritten annotations.
Semantic meaning
OCR cannot distinguish a $72,000 figure in a total row from the same value in a footnote reference.
GroundX understands what a value means based on its document context.
Reconciliation
OCR outputs require separate validation pipelines — adding cost and latency before results can be trusted.
ExtractX has reconciliation built in — every value is traced to its exact source location.
