Local PDF Toolbox

PDF Toolbox is a complete set of PDF tools that runs entirely on your iPhone. No account, no subscription, and nothing to buy — every tool is free. Your documents never leave your device. There is no server to upload to, so contracts, statements, and anything else private stays private. ORGANISE • Merge — combine several PDFs into one, in any order you like • Split — break one document into several, by page range or in fixed chunks • Organise pages — reorder, rotate, and delete pages with live page previews • Compress — reduce file size so a document is easy to email or upload CONVERT • Images to PDF — turn photos into a document, with each page sized to its picture • PDF to images — render any page as a PNG or JPEG, at up to 300 DPI SECURE & SIGN • Protect — add AES-256 password protection and choose what readers may still do • Unlock — remove a password you already know • Sign — draw your signature and place it anywhere on the page • Watermark — stamp text across every page, with a live preview as you adjust it • Page numbers — add numbering in the position, font, and size you choose READ & EXTRACT • Read — open, zoom, and search any PDF on your device • Extract text — pull selectable text out of pages and photos, including Latin, Chinese, Japanese, Korean, and Devanagari scripts BUILT FOR IPHONE Designed to feel at home on iOS, with grouped menus, familiar controls, and full light and dark appearance support. Large jobs run in the background so the app stays responsive, and any operation can be cancelled midway. PRIVATE BY DESIGN Text recognition uses on-device models. Nothing you open is uploaded, analysed, or shared, and we run no analytics of our own. FREE, WITH OPTIONAL ADS Every tool is free. Saving, opening, and sharing your finished documents never requires watching an ad. A short rewarded video is offered for a single convenience — sharing a large batch of exported images at once — and can always be skipped, since each image can be shared individually for free. That last paragraph is deliberate: it pre-answers the 2.1 question in the listing itself, so a future reviewer sees the model before asking.