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SafeRoute Guardian AI is a Python Streamlit web application that helps users plan safer travel routes and stay connected with trusted guardians. It combines route planning, safety scoring, location-based risk awareness, AI-assisted guidance, and notification workflows into a single interactive dashboard.

The app runs from streamlit_app.py and uses helper logic in app/streamlit_helpers.py, with SQLAlchemy models and service modules handling database access, route safety, AI responses, notifications, and guardian features. For local development, it is configured to use SQLite through a root .env file, making it easy to run as a demo or hackathon project.

In short: SafeRoute Guardian AI is a safety-focused navigation and guardian support tool designed to make travel decisions more informed, proactive, and secure.

Lifeline AI is an AI-powered emergency response platform providing real-time emergency intelligence, ambulance coordination, hospital connectivity, SOS management, and disaster response monitoring.

Project Overview: The CPU-First EMS is a highly resilient web platform designed specifically for distributed teams and field workers operating in environments with unreliable internet access.

Key Technical Achievements:

Offline-First Reliability: Implemented robust client-side storage to queue submissions and track attendance locally, ensuring zero data loss during outages and enabling automatic synchronization when reconnected.

Architectural Overhaul: Successfully migrated the application from a local Streamlit script to a scalable, production-ready REST API using Flask and Gunicorn with multi-threaded workers.

Modern User Experience: Built a responsive, dynamic frontend using Vanilla JavaScript and the Fetch API, styled with a modern glassmorphism aesthetic.

Production-Ready Deployment: Engineered a secure, multi-stage, non-root Docker build to streamline deployment and ensure consistent environments across local and production servers.

Chalo Miya! is an AI-powered Hyderabad travel companion that helps users discover places, build personalized itineraries, and explore the city's rich culture with intelligent recommendations.

MediScann — offline, CPU-first CLI that reads prescriptions and medical reports and uses a local LLM (ollama) to summarize the problem, list medications, suggest informational options, and flag warnings. No cloud, no telemetry.

Smart Bus Crowd Prediction System using Python and Flask for real-time seat occupancy monitoring, crowd analysis, and alternative bus recommendations.

Image Text Extractor — Offline OCR text extraction from images using Tesseract, local Llama post-processing, and SQLite history. 100% local, no cloud APIs.

MedKit Archive is a secure, offline health-tech application engineered to digitize handwritten prescriptions, medical forms, and laboratory reports using local AI engines. By processing all data completely on local machine resources, the platform eliminates reliance on external cloud servers, guaranteeing absolute data confidentiality and patient privacy. The application utilizes a powerful tech stack—including a streamlined Streamlit frontend interface, local Tesseract OCR for text extraction, Whisper for transcribing clinical audio consultations, and local Ollama large language models—to transform unstructured medical documents into patient-friendly explanations and queryable JSON structures. Built with robust regional multi-lingual fallback layers (supporting Telugu, Hindi, Tamil, and Kannada) and a structured SQLite backend, it provides a fully autonomous pipeline for secure medical record management.

Smart city intelligence and tourism platform for Hyderabad built with Streamlit, FastAPI, and AI-powered civic services.

LocalVital turns your messy health diary into a structured, private, queryable dataset — entirely on your device, no internet required.

Recruiters deal with hundreds of unstructured resumes in PDF and Word formats. Extracting consistent, comparable data requires expensive cloud AI APIs or tedious manual effort. This project proves that a local, quantized small language model (SLM) running on a commodity CPU can do the same job — privately, cheaply, and completely offline.

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.

LocalSlate is an offline-first, CPU-optimized AI incident processing system that converts unstructured text, audio, and voice reports into structured actionable data using a FastAPI backend, local AI workflow, and MySQL persistence.

Memento AI – A CPU-first, offline AI assistant that transforms documents, images, audio, video, and text into structured knowledge using local LLMs, SQLite, and Retrieval-Augmented Generation (RAG), with

SOP Guardian is an AI-powered tool that analyzes Standard Operating Procedures (SOPs), identifies compliance gaps, and provides actionable recommendations to improve accuracy, consistency, and regulatory adherence.

this is a offfline software runs on ollama

A smart application that converts unstructured medical documents into structured insights using OCR and intelligent data processing, making healthcare data easy to understand.

LedgerLens Drop in a photo or PDF of a receipt/invoice and get clean, structured ledger data — merchant, date, tax/GST, line items, and total — as JSON, exportable to CSV. Runs entirely on CPU and works with the network switched off.

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.

offline-first, AI-powered FIR draft assistant. Uses local LLMs (Ollama) and on-device OCR to ecurely extract structured data from sensitive complaint documents without the cloud.