A Python framework for multi-modal document understanding with Amazon Bedrock
-
Updated
Jun 19, 2025 - Python
A Python framework for multi-modal document understanding with Amazon Bedrock
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.
Leveraging the Robocorp integration to analyse customer feedback
Project Repository for Problem 1(b) of Adobe Hackathon 2025
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.
AI-powered document classifier using OCR, BERT, ResNet, and LayoutLMv3 for Aadhar, PAN, Passport, and other scanned IDs.
Add a description, image, and links to the intelligent-document-processing topic page so that developers can more easily learn about it.
To associate your repository with the intelligent-document-processing topic, visit your repo's landing page and select "manage topics."