A full-featured Document Management Platform / Document Layer for your application, providing storage, discovery, processing, and retrieval. Deploys directly into your Amazon Web Services Cloud. Please 🌟 star to support our work!

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

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

NeuroDoc is a powerful AI-based offline document summarization tool that leverages OCR and NLP to intelligently analyze PDFs and generate structured summaries. Built using Flask, this tool is designed to run completely offline and supports both text-based and scanned/image-based documents.

Boilerplate CSS that can be used with any Grooper DataModel

Leveraging the Robocorp integration to analyse customer feedback

AI-powered document classifier using OCR, BERT, ResNet, and LayoutLMv3 for Aadhar, PAN, Passport, and other scanned IDs.

SealSure is an AI-powered tool for real-time document validation and forgery detection. Built with MERN, FastAPI, and OCR/NLP models, it helps extract, analyze, and verify data from scanned or image-based documents efficiently.

An end-to-end serverless pipeline for Intelligent Document Processing (IDP) using Amazon Bedrock and Anthropic Claude 3 Sonnet. This project extracts structured data from scanned documents (e.g., PDFs, forms, invoices) using GenAI models, and stores results in a scalable cloud-native architecture.

Intelligent document processing (IDP) with AWS generative AI services to automate information extraction from documents of different types and formats, without the need for machine learning skills.