O

ollama

EndGame RAGHub is a scalable multimodal Retrieval-Augmented Generation platform supporting document, image, audio, and video understanding using FastAPI, Qdrant, LangGraph, and modern open-source AI infrastructure.

StudentAI - AI-powered RAG chatbot for document analysis and question answering using FastAPI, React, Ollama and Retrieval-Augmented Generation (RAG).

A Streamlit-based research paper assistant that uses AI (RAG + PyMuPDF4LLM) for document summarization, Q&A, and multimedia analysis with local-first inference via Ollama.

MyDocVault is a secure, offline-first AI platform designed to help users store, organize, understand, and manage government documents in a privacy-preserving environment. The application enables users to upload documents such as Aadhaar, PAN, Passport, Driving Licence, Voter ID, educational certificates, and other official records, while ensuring that all processing happens locally without relying on external servers or internet connectivity.

Powered by an intelligent document-aware assistant, MyDocVault extracts key information, summarizes documents in simple language, answers user queries based solely on locally stored documents, and provides guidance on the documents required for various government services. The system never fabricates information, clearly identifies missing details, and prioritizes user privacy by keeping all data offline.

Key Features 🔒 Offline-first and privacy-focused document management 📄 Secure storage and organization of government documents 🤖 AI-powered document understanding and summarization 🔍 Automatic extraction of important document details 📋 Government service document requirement guidance 📂 Intelligent document search and retrieval ⚠️ Identification of missing or incomplete documents 🛡️ Local processing with no external API or internet dependency 💬 Simple, conversational AI assistant for document-related queries 📊 Structured JSON extraction for document metadata

Tech Stack: React.js, Node.js, Express.js, SQLite, OCR, Local AI Models, HTML, CSS, JavaScript

Goal: To provide citizens with a secure, intelligent, and completely offline digital document vault that simplifies document management while ensuring maximum privacy and accessibility.

Smart Cab Finder is an AI-powered ride comparison platform that helps users compare fares, estimated arrival times, and ride options across multiple cab providers. The application includes an intelligent AI assistant for ride recommendations, supports Bring Your Own Key (BYOK) integrations, and is designed to support local AI inference through Ollama. To improve accessibility, the platform provides multilingual support in English, Hindi, and Telugu. Built using Python and Flask, the project follows secure development practices with automated testing, CI/CD pipelines, security scanning, and compliance-driven documentation.

Dream2Play AI is an AI-powered platform that transforms natural language prompts into playable games, stories, characters, missions, and worlds with support for cloud AI, local AI inference ( Ollama ), and BYOK.

PaperLens Offline is an offline-first, CPU-optimized AI research paper analyzer that extracts structured knowledge from academic PDFs using local LLMs (Ollama), stores the results in SQLite, and enables fast local search without any cloud APIs.

AI Medical Record Extractor is an offline-first web application that converts unstructured medical documents into structured JSON data using CPU-only inference. It supports PDF, image, and text files while ensuring complete privacy by processing all data locally without cloud services. Built with FastAPI, React, and SQLite, the application provides a user-friendly interface for extracting patient information, diagnoses, medications, and other medical details. The project is designed to be lightweight, secure, open source, and accessible in low-connectivity environments.

Offline Medical Report Structurer

Project Description

Offline Medical Report Structurer is an AI-powered healthcare application designed to transform unstructured medical reports into organized, structured, and easy-to-understand data without requiring an internet connection. The system processes medical documents such as laboratory reports, prescriptions, discharge summaries, and diagnostic reports, automatically extracting key information including patient details, diagnoses, medications, test results, and clinical observations.

By leveraging Natural Language Processing (NLP) and document parsing techniques, the application converts complex medical text into a standardized format that improves accessibility, readability, and data management. Since the solution operates entirely offline, it ensures patient privacy, data security, and usability in low-connectivity environments such as rural clinics, hospitals, and healthcare camps.

Key Features

Offline processing with no internet dependency Automated extraction of medical information Structured JSON/database output for easy integration Support for multiple medical report formats Secure and privacy-focused data handling Quick search and retrieval of patient information User-friendly interface for healthcare professionals

NyayaBloom is an AI-powered Judicial Intelligence Platform designed to democratize legal knowledge and improve judicial transparency across India. The platform enables citizens, lawyers, law students, researchers, journalists, and judicial professionals to access legal information, understand judicial processes, explore case precedents, and improve legal literacy through a multilingual AI-powered ecosystem. Instead of replacing judges, courts, or legal professionals, NyayaBloom serves as an intelligent legal knowledge assistant that simplifies legal information and promotes informed civic participation.

MedRepo is an offline, CPU-first AI application designed to convert medical Complete Blood Count (CBC) reports from PDFs or images into clean, structured JSON. The project prioritizes patient privacy by processing all data locally without requiring an internet connection or cloud services. It combines OCR and lightweight local language models to accurately extract and organize medical information for further analysis or integration with healthcare applications. Built with a modular architecture, MedRepo is easy to set up, extend, and maintain. The project aims to make medical report digitization faster, more secure, and accessible on low-resource devices while supporting future enhancements and broader diagnostic report formats.

Offline-first, CPU-first receipt and invoice OCR, local Qwen categorization, structured expense reporting, and JSON/CSV export.

LectureLens is a secure, localized, multi-modal ingestion pipeline that transforms raw educational assets into structured, high-retention study matrices. Built entirely on an offline-first philosophy, the system intercepts dense lecture audio streams and multi-page technical PDFs, running them through an isolated edge-computing layer to generate interactive flashcards, core concept maps, and dynamic glossaries without leaking sensitive user data to third-party cloud vectors.

Lightweight local-first RAG chatbot built with Streamlit, Ollama, ChromaDB, SQLite, and local quality checks.

Local-First Document Q&A with RAG using Ollama — Find-Retrieve-Answer pattern

AI Document Assistant - A local-first RAG chatbot built with Streamlit, LangChain, Ollama, and ChromaDB for PDF question answering, OCR, summarization, and resume analysis.

TravelSathi is an AI-powered travel planning assistant developed for the Swecha Hackathon. It combines Retrieval-Augmented Generation (RAG), offline local language models (via Ollama), and multilingual support to generate personalized itineraries, budget estimations, local phrases, and destination recommendations.

🚀 VidyaVaani - Revolutionary AI-Powered Teacher's Assistant for Regional Schools

VidyaVaani is a cutting-edge, production-ready AI education platform that democratizes artificial intelligence for India's diverse linguistic landscape. Built with enterprise-grade architecture and powered by state-of-the-art open-source AI models, this platform bridges the digital divide by bringing advanced AI capabilities to government and rural schools.

🌟 Key Features: • Multilingual AI Excellence: Native support for 12+ Indic languages (Hindi, Telugu, Tamil, Kannada, Bengali, Marathi, Gujarati, Punjabi, Odia, Malayalam, Assamese) • Open Source AI Engine: Integration with Ollama, Gemma, Llama, and Mistral models for unlimited, cost-free AI processing • Smart Document Processing: AI-powered text extraction from PDFs, images, and documents • Dynamic Content Generation: Automated creation of quizzes, explanations, translations, and Q&A sessions • Voice-First Interface: Voice commands and TTS in regional languages • Production-Ready Architecture: Docker, Redis caching, Celery task queuing

Technical Stack: • Frontend: Streamlit with modern UI/UX • Backend: Flask REST API with JWT authentication • AI Integration: Local AI models via Ollama with cloud fallbacks • Database: SQLAlchemy with SQLite • DevOps: Docker Compose, production scripts, CI/CD templates

🎯 Impact & Vision: Empowers millions of teachers across India with AI co-pilots that understand their cultural and linguistic context. VidyaVaani is a revolution in educational technology that makes AI accessible, affordable, and culturally relevant for every Indian classroom.

🔬 Research & Innovation: Perfect for AI education research, multilingual model development, and educational technology innovation. Open-source architecture enables community contributions.

Built with ❤️ for India's educational excellence by the Swecha community.