docling-project/doclingGitHub
calls deepdoctection “if you want a framework to build custom document AI pipelines rather than a one-shot parser”
Get your documents ready for gen AI
66.4kPythonactive
deepdoctection/deepdoctection Alternatives
deepdoctection is queued for analysis. Crawling candidates and ranking them takes a few minutes. This page updates itself when the list exists — you can also come back later.
What is known so far comes from the other direction:
Listed as an alternative to
These projects were analysed and named deepdoctection among their alternatives. The relationship is not symmetric — how deepdoctection rates them is a separate judgement, made when deepdoctection is analysed in its own right.
datalab-to/markerGitHub
calls deepdoctection “When you want a modular framework to build custom document AI pipelines with fine-grained control.”
Convert PDF to markdown + JSON quickly with high accuracy
39.0kPythonactive
JaidedAI/EasyOCRGitHub
calls deepdoctection “Choose when you are building a document AI pipeline that orchestrates OCR, layout, and other models, not as a direct OCR drop-in.”
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
29.9kPythonslowing
datalab-to/suryaGitHub
calls deepdoctection “modular framework to combine multiple document AI models rather than a single integrated one.”
OCR, layout analysis, reading order, table recognition in 90+ languages
21.3kPythonactive
firecrawl/anydocGitHub
calls deepdoctection “Document AI framework; choose for building custom OCR/layout pipelines rather than drop-in conversion.”
Convert Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, and PDF to clean Markdown. Built in Rust, with Node.js and Python bindings.
19.8kRustactive
Unstructured-IO/unstructuredGitHub
calls deepdoctection “when you need a customizable document AI framework for building your own extraction pipelines with DL models.”
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
15.3kHTMLactive
xberg-io/xbergGitHub
calls deepdoctection “when you need a Python document-AI framework with pluggable layout/table/OCR models and fine-grained control.”
A polyglot document intelligence framework with a Rust core. Extract text, metadata, images, and structured data from 101 formats (115 file extensions) plus code intelligence for 371 code languages. 15 language bindings — Rust, Python, Ruby, Java, Go, PHP, Elixir, C#, TypeScript — plus CLI, REST API, and MCP server.
9.2kRustactive
clovaai/donutGitHub
calls deepdoctection “choose when you need a full document-AI pipeline with layout and OCR components rather than a single OCR-free model.”
Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022
6.9kPythondormant
NanoNets/docstrangeGitHub
calls deepdoctection “choose when you need to build a custom document AI pipeline with your own models; not a ready-to-use converter.”
Extract and convert data from any document, images, pdfs, word doc, ppt or URL into multiple formats (Markdown, JSON, CSV, HTML) with intelligent structured data extraction and advanced OCR.
1.5kPythonslowing