All-in-one client-side PDF suite. Merge, split, rotate, organize pages, compress files, convert images, extract digital text, and add security watermarks.
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Explore PDF document architecture, page extraction, linear merging, metadata hygiene, and local client-side processing security without server data exposure.
The PDF Toolkit is a comprehensive, client-side document workstation for merging multiple PDFs, organizing and rotating pages, splitting ranges, compressing documents, converting between images and PDFs, extracting digital text, watermarking, and metadata management.
Processes documents entirely client-side using pdf-lib and WebAssembly. Manipulates PDF objects, cross-reference tables, and content streams directly in browser memory without sending private files to external cloud servers. Stamps watermarks, flattens interactive forms, and optimizes internal stream structures.
inv1.pdf (2 pages), inv2.pdf (1 page), inv3.pdf (3 pages)merged_invoices.pdf (6 pages, numbered "Page X of 6" bottom-center)Merges all three documents in custom order, compiles the global page count, and stamps pagination across all pages.
receipt1.jpg, receipt2.png, form.webpcompiled_receipts.pdf (3 pages, fitted to A4 format)Converts disparate image formats into a single, standardized multi-page PDF document locally.
No. Outlivo PDF Toolkit operates client-side inside your browser sandbox using pdf-lib and WebAssembly. Documents, contracts, and files are not uploaded to an Outlivo application server for processing.
The Text Extractor reads uncompressed digital text streams directly from vector-encoded PDFs. For image-only scans or documents using proprietary font encodings, characters cannot be read without raster OCR software.
Yes! The Watermark tab allows you to stamp customized text watermarks, diagonal security notices, headers, footers, and dynamic page numbering across all pages or selected page ranges.
The compressor strips unreferenced resource streams, consolidates redundant font descriptors, and recompresses internal content dictionaries using FlateDecode. Documents containing heavy high-resolution images are scaled to standard screen DPI.