Open-source alternatives to Zerox

Dolphin is a multimodal layout analyzer and image-to-structure converter that transforms photographed or digital document images into machine-readable structured data. It functions as an LLM document parser, utilizing vision-language models to simultaneously predict spatial layout and text content. The system is designed as a concurrent document processor, employing parallel document parsing to process multiple elements across distributed compute nodes. This high-throughput approach reduces the total time required to convert large volumes of images into structured formats. The project covers

pdf2htmlEX is a PDF to HTML converter that transforms documents into web pages while preserving the original layout, fonts, and formatting. It functions as a layout engine and text extractor, mapping PDF coordinate data to HTML and CSS to maintain visual fidelity. The tool converts PDF content into searchable and selectable native HTML text by embedding original document fonts. It maintains document interactivity by preserving internal links, bookmarks, and outlines, converting them into functional web navigation. The conversion process supports flexible output structures, allowing documents

Nougat is a neural OCR system and LLM document parser designed to convert images of academic PDF documents into structured markdown text and mathematical formulas. It functions as a PDF to markdown converter that uses deep learning to handle layout and formula recognition. The project provides a document training pipeline for generating datasets and training neural networks to recognize specific academic document styles. This includes utilities for training dataset generation, neural model training, and model checkpoint management to ensure reproducible deployment. The system covers a broad

LEANN is a framework for local retrieval augmented generation and vector indexing. It functions as a system for building local knowledge bases and source code search engines that combine large language models with retrieved private data to generate context-aware responses. The project distinguishes itself through a vision-model based document layout extractor for parsing complex PDF figures and diagrams, and a source code search engine that employs structure-aware chunking to preserve function and class boundaries. It also implements the Model Context Protocol to integrate real-time data sour

Pix2Text is an optical character recognition system and document conversion tool designed to transform images and PDFs into Markdown. It functions as a multilingual OCR engine supporting over 80 languages, a LaTeX formula recognizer for mathematical notations, and a parser integrated with vision language models. The project utilizes a hybrid pipeline to separate plain text from mathematical formulas and tabular structures within a single pass. It converts recognized formulas into LaTeX expressions and transforms detected tables and layouts into structured Markdown formatting. The system incl

Olmocr is a distributed document processing framework designed to convert PDF and image files into structured markdown. It functions as a vision-based document parser that utilizes multimodal neural networks to interpret complex visual layouts and translate them into standardized text representations. The system operates as a remote inference orchestrator, offloading heavy document analysis tasks to external servers or cloud APIs to minimize local computational requirements. By employing a stateless worker architecture, it decouples document ingestion from inference, allowing for the distribu

Kreuzberg is a document extraction engine that converts PDFs, Office files, images, and over 90 other formats into clean, structured text and metadata. It is built around a compiled Rust core that can be used as a native library, a command-line tool, a REST API server, or a WebAssembly module for browser-based processing. The system is designed to run entirely on self-hosted infrastructure, with no data leaving the user's environment. What distinguishes Kreuzberg is its breadth of integration surfaces and its pipeline architecture. It exposes extraction capabilities through native bindings fo

sChandra is a document processing platform that converts images, PDFs, Word documents, spreadsheets, and other formats into structured output such as HTML, Markdown, or JSON while preserving layout. It can also extract specific data fields from invoices, contracts, or reports using user-defined JSON schemas, with citations back to source locations. The service supports form filling in PDF and image documents, document generation from Markdown, and extraction of tracked changes from Word files. The platform distinguishes itself with pipeline-based processing chains that combine multiple proces

Sparrow is an LLM document extraction platform and vision-based inference engine designed to convert images and PDFs into validated structured data. It functions as an agentic workflow orchestrator that chains classification, extraction, and validation tasks into multi-step pipelines. The system distinguishes itself through a backend-agnostic inference layer that manages models across local GPUs, Apple Silicon, and cloud providers. It employs coordinate-based visual grounding to map extracted text to precise bounding box coordinates and utilizes hint-based model steering to guide attention an

Megaparse is a document parsing tool and RAG data preprocessor designed to convert PDFs, Word documents, and presentations into clean text formats. It functions as a vision-based document extractor that recovers high-fidelity information from images and complex layouts to optimize data for large language model ingestion. The system employs multimodal AI and vision models to perform schema-preserving parsing, which maintains structural hierarchies such as tables and headers. It utilizes lossless structural transformation to turn layout-heavy binary files into text sequences while preserving th

This project is an AI-powered document processing engine designed to transform diverse file formats into structured Markdown. By leveraging multimodal language models, it performs complex layout analysis and semantic text extraction, allowing for the conversion of both unstructured files and scanned images into machine-readable content. The toolkit distinguishes itself through a modular, plugin-based architecture that orchestrates multi-stage extraction pipelines. Users can steer the parsing behavior by injecting custom instructions, enabling the system to adapt to domain-specific document st

GOT-OCR2.0 is an end-to-end optical character recognition system and document text extractor. It utilizes a unified transformer architecture to recognize and extract plain and formatted text from diverse images and documents. The system features a multi-crop processing method that divides high-resolution or dense documents into smaller sections to maintain recognition detail. It also includes a renderer that transforms recognized text into HTML to preserve the original structure and layout of the document. The project provides a framework for fine-tuning pre-trained models on custom datasets

dots.ocr is a suite of software utilities for document layout analysis, multilingual optical character recognition, and scene text digitization. It functions as an engine for extracting digital text and structured layout data from images and PDFs across various human scripts. The project includes a specialized transformer for converting charts, diagrams, and chemical formulas from raster images into scalable vector graphics. It also provides a pipeline to transform extracted text and structural layout from documents and web screenshots into formatted Markdown files. The system covers capabil

Marker is an LLM-powered document parser and OCR pipeline designed to convert PDFs and unstructured files into structured markdown, JSON, and HTML. It functions as a data preprocessor that transforms complex documents into machine-readable formats while preserving tables, equations, and layout structures. The system utilizes large language models to refine OCR accuracy, clean mathematical notation, and merge fragmented tables across multiple pages. It employs model-based layout analysis to predict block types and bounding boxes, ensuring a more precise conversion of document elements. Capabi

This project is a comprehensive framework and toolkit for developing, optimizing, and deploying transformer-based models across multimodal, document intelligence, and natural language processing tasks. It provides a unified neural architecture that processes text, vision, audio, and document layout data through a shared set of weights, enabling researchers and developers to build foundational models that align cross-modal representations. The platform distinguishes itself through advanced training and inference strategies designed for large-scale deep learning. It incorporates specialized mec

Unstructured is an enterprise-grade data orchestration engine designed to transform raw, unstructured files into structured, machine-readable formats. It functions as a comprehensive platform for document ingestion, partitioning, and enrichment, specifically engineered to prepare complex data for retrieval-augmented generation and agentic AI workflows. The platform distinguishes itself through its sophisticated document processing strategies, which combine rule-based extraction with vision-language models to handle diverse file layouts, tables, and images. It provides a modular architecture t

Tesseract is an optical character recognition engine and tool designed to convert printed or handwritten text from images into machine-readable digital text. It functions as a multilingual text extractor and a document digitization pipeline that transforms scanned images into structured digital formats. The project includes a framework for training custom scripts and language-specific models, allowing the engine to recognize new languages or unique fonts through custom training data. Its capabilities cover automated text extraction, digital archive digitization, and the export of recognized

PDFPatcher is a specialized suite of PDF utility tools designed for editing navigational bookmarks, modifying document structure, managing metadata, and processing pages. It provides a toolkit for altering PDF structures and properties without changing the original content stream. The project is distinguished by its focus on bookmark management, featuring bulk editing and the ability to generate clickable bookmarks from visual tables of contents using optical character recognition. It also includes capabilities for font optimization through substitution and embedding to ensure consistent char

Upsonic is a Python framework and orchestrator for building autonomous AI agents. It provides the infrastructure to develop self-operating systems that execute complex workflows and manage tasks independently using a scripting language. The project functions as an agentic tool integration layer, connecting agents to third-party data sources and external service APIs through standardized communication protocols. To ensure security, it includes an isolated execution environment that restricts shell and file operations to a specific workspace to prevent path traversal and dangerous commands. Ad

Paper2gui is a multi-modal AI toolkit and model GUI wrapper designed to deploy and run various artificial intelligence models through a visual interface. Its primary purpose is to provide a way to execute complex AI research papers and models without requiring manual software installation or coding. The project distinguishes itself by using a wrapper-based model interface that abstracts command line arguments into visual input fields, utilizing template-driven UI generation to create parameter sliders and forms based on the specific requirements of the underlying model. It includes a centrali

This project is a Python framework for building autonomous AI agents capable of executing independent tasks through goal-oriented instructions. It provides a library of tools for managing system operations and processing multimodal data. The framework features a sandboxed system execution environment that restricts shell commands and file access to protect the host system. It also includes an automated OCR text extraction pipeline for converting printed or handwritten text from images and documents into digital formats. Connectivity is handled through a modular tool integration system and a

Jo is a command-line utility designed to construct and manipulate JSON objects and arrays directly from shell arguments and standard input. It functions as a data processing tool that transforms raw input into structured formats, enabling the generation of complex payloads for APIs, configuration files, and automated data pipelines. The tool distinguishes itself through its ability to resolve hierarchical data structures using delimiter-based path definitions and its integrated type-inference engine, which automatically casts input values into native boolean, numeric, or null types. Users can

Docling is a multimodal content converter and document parser designed to transform PDFs, Office files, and HTML into structured Markdown or JSON for generative AI applications. It functions as an OCR document processor and a PDF layout analyzer that extracts tables, charts, and hierarchical structures while preserving the original page layout. The system operates as a local-first inference engine, allowing for the processing of sensitive data in air-gapped environments without external network connectivity. It can also be deployed as an API or a Model Context Protocol server to provide parsi

MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW

omniparser: a native Golang ETL streaming parser and transform library for CSV, JSON, XML, EDI, text, etc.