Document OCR and Structured Extraction Tools

Extract text, Markdown, JSON, tables, captions, and RAG-ready chunks from scanned PDFs and document images with OCR and structure-aware workflows.

This hub focuses on turning document files into reusable data. It covers image OCR, scanned-PDF recovery, plain-text and Markdown extraction, structure-aware JSON browsing, table export, caption indexing, page-range extraction, and chunk packaging for downstream search or LLM pipelines.

Cluster Facts

Task Type
extract
Families
ocr, pdf, document
Tools
13
Subclusters
3

Why this hub exists

Document extraction is rarely a single step. Teams often need OCR first, then a clean export in Markdown, JSON, CSV, or text depending on the downstream workflow.
Keeping OCR, PDF parsing, table extraction, and structure-aware export tools together makes it easier to compare the right extraction path for reports, receipts, IDs, contracts, and scanned archives.
The included PDF and image samples let users test recognition quality and output structure before they run the same workflow on real business documents.

Featured Tools

AI Image to Markdown
Extract text from images and convert to markdown format using AI vision models
Receipt & Invoice OCR Recognition
Extract key information from receipt/invoice images and convert to custom JSON format using AI vision models
AI ID Card OCR Recognition
Extract key information from ID card images and convert to JSON format using AI vision models for free
PDF OCR Text Layer
Add searchable/copyable OCR text layer to scanned PDF using Tesseract
Scanned PDF OCR to Markdown
Convert scanned or image-heavy PDFs into Markdown with OpenDataLoader hybrid OCR, with a graceful fallback when the hybrid backend is unavailable
PDF Text Extractor
Extract text content from PDF documents with support for page selection, formatting options, and multi-language processing
PDF to Markdown Converter
Convert PDF documents to Markdown format with text extraction and formatting preservation
PDF to Clean Text for LLM
Extract clean text from PDFs with OpenDataLoader for summarization, translation, embedding, and other LLM workflows
PDF to JSON Structure Explorer
Extract structured OpenDataLoader JSON from a PDF and browse headings, paragraphs, tables, lists, pages, and bounding boxes in an explorer view
PDF Table Extractor to CSV/JSON
Extract tables from PDFs with OpenDataLoader and export them as structured JSON, flat CSV, or HTML tables
PDF RAG Chunker & Citation Pack
Convert a PDF into heading-aware RAG chunks with page numbers, bounding boxes, and citation metadata
PDF Image & Caption Extractor
Extract images from PDFs, match nearby captions, and generate an HTML index package using OpenDataLoader
PDF Page Range Extractor
Extract only selected PDF pages with OpenDataLoader and export the subset as Markdown, JSON, or text

Try with Samples

ocr, pdf, document
PDF Samples
Generated PDF samples from tools dated 2026-02-01 to 2026-02-10
26 Samples
ocr, pdf
JPG Samples
Sample JPG images in different aspect ratios and resolutions
12 Samples
ocr, pdf
PNG Samples
Sample PNG images in different aspect ratios and resolutions
12 Samples
ocr, pdf
TIFF Samples
Sample TIFF images in different aspect ratios and themes with high-quality uncompressed format
8 Samples
ocr, pdf
JSON Samples
JSON (JavaScript Object Notation) format examples from simple to complex structures
10 Samples
ocr, pdf
Markdown Samples
Markdown format examples from simple to complex document structures
4 Samples
ocr, pdf

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Markdown Export, OCR, and Document Conversion Tools
Compare Markdown-to-PDF, PDF-to-Markdown, OCR, slide deck export, and structured Markdown conversion tools in one hub for documentation publishing workflows.
JSON Interchange and Format Translation Tools
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FAQ

What can I do in this hub?

You can OCR images and scanned PDFs, extract clean text or Markdown, inspect structured JSON output, export tables, capture captions, slice page ranges, and package documents for RAG or LLM workflows.

Who is this hub for?

It is useful for researchers, operations teams, knowledge-base builders, AI pipeline developers, and anyone who needs to turn documents into machine-usable content.

How should I start?

Start with the sample closest to your source document type, then choose between OCR, text cleanup, Markdown export, JSON inspection, or table extraction based on the output you need next.