NanoNets/docext

Health v2 · maintenance only

Adoption not part of the score

2085 stars · 155 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

docext is an on-premises document intelligence toolkit powered by vision-language models, offering OCR-free structured data extraction, PDF/image-to-markdown conversion, and a benchmarking leaderboard for document processing tasks. It is a Python library (pip-installable) from NanoNets that also ships the Nanonets-OCR-s model for image-to-markdown conversion.

Use cases

• extract structured fields from invoices and passports without OCR
• convert PDFs and scanned images to markdown with tables and LaTeX equations
• detect signatures and watermarks in documents
• benchmark vision-language models on document extraction tasks
• run document data extraction fully on-premises for privacy
• extract tables from unstructured documents with confidence scores

When to choose

• you need on-premises/private document extraction without sending data to cloud APIs
• you want OCR-free structured extraction using vision-language models
• you need PDF/image to markdown conversion with semantic tagging
• you want to benchmark VLMs on IDP tasks like KIE and table extraction

When to avoid

• you need a lightweight traditional OCR engine like Tesseract
• you lack GPU resources for running vision-language models
• you only need simple text extraction from digital PDFs
• you need a managed cloud service with SLAs

Facets

library · maturity active

ocr nlp machine-learning pdf benchmarking rag machine-learning pdf developer-tools artificial-intelligence python self-hosted cross-platform vision-language-models document-intelligence information-extraction markdown-conversion on-premises key-information-extraction table-extraction idp-leaderboard natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="NanoNets/docext")