Table recognition
Uses row grouping and inferred column anchors to build more usable spreadsheets from PDF text.
Spreadsheet extraction
Spreadsheet-friendly exportColumn anchor inferenceNo file upload requiredPull tables and structured rows into an Excel workbook. Phase 1 focuses on local spreadsheet extraction rather than full table-reconstruction fidelity.
Preview pages, inspect inferred rows and columns, then generate an XLSX workbook locally.
Choose the PDF with tables or data. The file is loaded into your browser session for local processing.
The engine groups text into lines, infers repeating column anchors, and maps rows into spreadsheet-friendly worksheets.
The Excel file is generated locally and prepared for download in the same session.
The workflow groups text into spreadsheet rows and infers stable column anchors for more consistent worksheet columns.
Structured worksheet output is generated locally for review in Excel, Sheets, or compatible tools.
Financial or operational data stays in the browser session during standard extraction workflows.
Extract financial or operational data locally without a separate third-party upload step for standard workflows.
Output preserves table-like structure where repeated row and column patterns are visible in the source PDF.
Exact table reconstruction still depends on the source PDF. The page states that boundary instead of overpromising.
Extracting tables from PDF files is common for reporting and analysis. Many tools require uploading sensitive files to remote servers. DocuStitch removes that step for standard workflows.
With DocuStitch, extraction runs in your browser session using WebAssembly (WASM), so table data stays on your device during processing.
The current engine groups page text into rows, infers repeating column anchors, and builds worksheet output that is easier to edit and review in Excel.
Uses row grouping and inferred column anchors to build more usable spreadsheets from PDF text.
Infers repeated column positions to place extracted text more consistently across rows.
Extraction runs in your browser session instead of a remote upload queue.
Starts quickly without waiting for a remote upload queue.
DocuStitch is designed for local-first processing. For standard workflows, data stays in your browser session during extraction.
The current workflow is heuristic, but it uses inferred column anchors in addition to row grouping. Exact reconstruction depends heavily on the source PDF.
Yes, but scanned content may require OCR processing and results depend on scan quality.
No. The exported .xlsx file can be opened in Excel, Google Sheets, LibreOffice, and other compatible tools.
No. The workflow runs in modern browsers with WebAssembly support.