pdf2docx

pdf2docx

Artifex
+
+

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About

Docling is an easy-to-use, self-contained, MIT-licensed open source toolkit for converting messy documents into structured data and simplifying downstream document and AI processing. It can parse many popular document formats into a unified and richly structured Docling Document, including PDF, DOCX, PPTX, XLSX, HTML, Markdown, AsciiDoc, CSV, images, audio, and scanned pages through an OCR engine of the user’s choice. Docling detects tables, formulas, reading order, chunks, bounding boxes, page headers and footers, pictures, captions, code, list items, paragraphs, cells, and document structure, making extracted content easier to process, search, and ingest into AI, RAG, and agentic systems. It can export parsed documents to JSON, text, Markdown, HTML, and Doctags, giving developers flexible outputs for pipelines and applications. Docling stores and traverses components according to reading order, partitions documents into bite-sized contiguous text chunks.

About

pdf2docx is a Python library that uses PyMuPDF to extract data from PDF files, parse their layouts according to rules, and generate corresponding .docx files via python-docx. It supports conversion of text, images, tables, and other structural elements; it includes tools to extract tables, handle formatting, and preserve layout as much as possible. It offers both a command-line interface and a graphical user interface. The internal architecture is modular; it includes packages for handling pages, layout, tables, images, shape paths, text spans/blocks, and other elements, enabling fine control over how PDF content is mapped into Word documents. Developers can use the API for batch conversions or integrate it into workflows; there's documentation on installation (from PyPI or source), usage, and technical details of layout-parsing, table extraction, and internal modules. The project is open source, hosted on GitHub, and made available under its license with no warranty.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI teams that want to convert complex documents into structured data for document processing, RAG, and agentic applications

Audience

Technical users seeking a solution to convert PDF documents into Word format programmatically while preserving layout, tables, images, and text structure

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Docling
United States
www.docling.ai/

Company Information

Artifex
Founded: 1993
United States
pdf2docx.readthedocs.io/en/latest/

Alternatives

DeepSeek-OCR

DeepSeek-OCR

DeepSeek

Alternatives

AnyParser

AnyParser

CambioML
Mistral OCR 3

Mistral OCR 3

Mistral AI
Mistral OCR 4

Mistral OCR 4

Mistral AI
PDF.co

PDF.co

ByteScout
Unsiloed

Unsiloed

Unsiloed.ai
PDF Conversa

PDF Conversa

ASCOMP Software

Categories

Categories

PDF

Integrations

Python
GitHub
Google Sheets
HTML
JSON
Markdown
Microsoft Excel
Microsoft Word
Model Context Protocol (MCP)
PyMuPDF
PyPI

Integrations

Python
GitHub
Google Sheets
HTML
JSON
Markdown
Microsoft Excel
Microsoft Word
Model Context Protocol (MCP)
PyMuPDF
PyPI
Claim Docling and update features and information
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