Document to Markdown - PDF, Word, PowerPoint, Excel, HTML, EPUB & images for LLMs and RAG

Convert documents into clean Markdown, plain text and RAG-ready chunks. Give URLs (or upload files) and get one dataset item per document with the Markdown, headings outline, tables, metadata, page numbers and, if you want, overlapping chunks that remember their page range and heading path.

Format	What you get
PDF	Reading order (two-column pages handled), headings from font sizes, lists, tables, running headers/footers removed, hyphenation repaired
Scanned PDF / images (PNG, JPG, TIFF incl. multi-page, WEBP, BMP, GIF)	OCR with Tesseract (default English + Spanish, 100+ languages selectable)
DOCX	Headings, lists, tables, bold/italic/links; title and author from properties
PPTX	One section per slide (title, bullets, tables, speaker notes), slide numbers as pages
XLSX / XLS / ODS / CSV	Each sheet as a Markdown table, dates formatted
HTML	Main content only (navigation, cookie banners and ads stripped)
EPUB	Chapters in reading order with book metadata
TXT / Markdown	Passed through

Also supported: public Google Drive, Dropbox and Google Docs / Sheets / Slides share links.

Everything runs on permissively licensed open-source libraries (pdf.js, mammoth, SheetJS CE, Tesseract.js, turndown); no AGPL code, no external API, no API key.

Input example

{
  "urls": [
    { "url": "https://example.com/annual-report.pdf" },
    { "url": "https://example.com/handbook.docx" }
  ],
  "enableChunking": true,
  "chunkSize": 1000,
  "chunkOverlap": 100,
  "ocr": "auto",
  "ocrLanguages": "eng+spa"
}

Useful options: maxPagesPerDocument (cap cost on huge files), includePages (Markdown per page / slide / sheet), ocr (auto = only pages without a text layer, always, never), pdfPassword (secret), maxFileSizeMb.

Output example

{
  "id": "7c1d0f4a9b21",
  "fileName": "annual-report.pdf",
  "fileType": "pdf",
  "status": "ok",
  "title": "Annual Report 2025",
  "author": "ACME Corp",
  "language": "en",
  "unit": "page",
  "pageCount": 48,
  "pagesProcessed": 48,
  "ocrPages": 0,
  "wordCount": 21873,
  "tableCount": 14,
  "markdown": "# Annual Report 2025\n\n## Letter to shareholders\n\n...\n\n| Region | Revenue | Growth |\n| --- | --- | --- |\n| North | 1,200,000 | 8% |",
  "headings": [{ "level": 1, "text": "Annual Report 2025", "page": 1 }],
  "chunks": [{ "index": 3, "text": "...", "charCount": 934, "pageStart": 2, "pageEnd": 3, "headingPath": ["Annual Report 2025", "Letter to shareholders"] }],
  "metadata": { "creator": "InDesign", "createdAt": "2026-01-15T10:00:00Z" }
}

Failed documents appear with status: "failed" and an error, and are not charged. The run's SUMMARY record lists pages processed, OCR pages and errors.

Pricing

Event	Price	When
page-processed	US$0.50 per 1,000 pages	every PDF page, slide, image; about 3,000 characters for flowing formats (DOCX, HTML, EPUB, TXT, spreadsheets)
ocr-page	US$10 per 1,000 pages	extra, only for pages read with OCR (scans, images)

A 40-page text PDF costs US$0.02. A 40-page scan costs US$0.42. Use maxPagesPerDocument and the run's maximum-cost setting to cap spending; the Actor stops cleanly at the limit.

FAQ

How good is table extraction? Tables in text PDFs are detected from column alignment and converted to Markdown tables; simple grids are reliable, merged-cell or borderless layouts are best effort. DOCX, PPTX, HTML and spreadsheet tables are exact.

Is my file stored? No. Downloads are deleted after conversion; only the result is saved in your run.

Scanned document with columns or stamps? OCR returns text per paragraph; very noisy scans reduce accuracy. Choose the right ocrLanguages for best results.

Can it read old .doc / .ppt? Not directly; save them as .docx / .pptx or PDF.

Why use chunks from here? Each chunk carries pageStart, pageEnd and headingPath, so retrieval results can cite the page and section.

Use cases

RAG ingestion, LLM context preparation, document search, contract and report analysis, archive digitisation, data extraction from public filings, knowledge-base migration.

En español

Convierte PDF, Word, PowerPoint, Excel/CSV, HTML, EPUB e imágenes en Markdown limpio, texto plano y chunks para RAG (con número de página y ruta de títulos). Los PDF escaneados y las imágenes se leen con OCR (inglés y español por defecto, más de 100 idiomas). Mantiene tablas, quita encabezados y pies repetidos y soporta enlaces de Google Drive y Dropbox. Precio: US$0,50 por 1.000 páginas, más US$10 por 1.000 páginas con OCR. No necesita API key; los archivos se borran al terminar.