document-processing topic

Retrieval of fully structured data made easy. Use LLMs or custom models. Specialized on PDFs and HTML files. Extensive support of tabular data extraction and multimodal queries.

parsee-ai

A Python framework for multi-modal document understanding with Amazon Bedrock

awslabs

Plug-and-play, zero-shot document AI pipelines.

MantisAI

Open-source toolkit to extract structured knowledge graphs from documents and tables — power analytics, digital twins, and AI-driven assistants.

Addepto

Enterprise-ready vector database toolkit for building searchable knowledge bases from multiple data sources. Supports multi-project management, automatic ingestion from Confluence/JIRA/Git, intelligen...

martin-papy

A Model Context Protocol (MCP) server implementation exposes document processing capabilities through natural language, supporting both direct human interaction and AI agent tool calling.

PSPDFKit

⚡ Production-ready .NET Standard 2.1 RAG library with 🤖 multi-AI provider support, 🏢 enterprise vector storage, 📄 intelligent document processing, and 🗄️ multi-database query coordination. 🌍 Cros...

byerlikaya

Conversion of PDF documents to structured Markdown, optimized for Retrieval Augmented Generation (RAG) and other NLP tasks. Extract text, tables, and images with preserved formatting for enhanced info...

iamarunbrahma

This repository contains examples for customers to get started using Amazon Bedrock Data Automation. The samples focus mainly on document processing use cases

aws-samples

📄 Production-ready MCP server for PDF processing - 5-10x faster with parallel processing and 94%+ test coverage

SylphxAI