Extract text from images — free

The converter rebuilds the document's logical structure — headings, paragraphs, lists, real <table> elements, links and images — rather than just pinning each character at an X/Y coordinate the way some PDF viewers do. The result reflows on mobile, indexes well for SEO, and is screen-reader accessible out of the box.

Yes. Tables become standard <table>, <thead>, <tbody>, <tr>, <th> and <td> elements with proper scope attributes on header cells. That makes them screen-reader friendly, searchable, and easy to style with Bootstrap, Tailwind, or your existing CSS framework — no extra markup transformation needed.

Yes. Paste into WordPress, Webflow, Ghost, Notion (as embed), Confluence, GitBook or your custom static site — the markup is dependency-free, validates against the W3C HTML5 spec and renders identically across Chrome, Safari, Firefox and Edge. Images are inlined as base64 or extracted as separate files depending on your preference.

Yes. Image-only PDFs trigger the OCR engine, which extracts text and rebuilds the layout before generating HTML. That means even old scanned whitepapers, photographed reports and faxed-back documents can be republished as modern responsive web pages with proper headings, paragraphs and links.

Yes. Embedded images are extracted, optimized (WebP or PNG depending on content), and referenced via <img> tags with width and height attributes set for CLS-friendly loading. Vector charts may flatten to a raster — for full vector fidelity, use PDF to Images and embed the SVG renditions manually.

Uploads are deleted within minutes, never used to train models, never shared. The HTML output has no watermark, no attribution comment, no tracking pixel. Agencies and in-house teams use the tool to migrate legacy PDFs into modern CMS sites without any licensing or privacy concerns.