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The AI-Driven Crop Disease Prediction and Management System is an intelligent agricultural platform designed to help farmers detect, analyze, and manage crop diseases at an early stage using artificial intelligence and computer vision.

The system allows users to upload images of crops or capture them in real time through a camera. Using advanced deep learning and image processing techniques, the model identifies diseases affecting leaves, stems, or fruits and provides accurate predictions along with confidence scores.

Beyond detection, the system goes further by offering actionable agricultural insights, including treatment recommendations, preventive measures, pesticide suggestions, and crop care guidance. This transforms the application from a simple detection tool into a complete decision-support system for farmers.

The platform can also integrate weather data, soil conditions, and historical crop patterns to improve prediction accuracy and provide context-aware suggestions. A user-friendly dashboard ensures that farmers and agricultural experts can easily interpret results without technical complexity.

Key Features: 🌿 Real-time crop disease detection using image input 🧠 AI-based classification of plant diseases 📊 Confidence score and severity analysis 💊 Treatment and prevention recommendations 🌦️ Optional integration with weather and soil data 📱 Simple and accessible web/mobile interface 📈 Analytics dashboard for crop health monitoring Objective:

To empower farmers with early disease detection and smart recommendations, reducing crop loss, increasing yield, and enabling data-driven agriculture.

The Tax Transparency Tracker is an AI-powered web app that helps Indian citizens see exactly how their income tax is being spent by the government. Users can simply enter their income to get a personalized breakdown of their contributions across key sectors and track local government-funded projects on an interactive map. It features a Gemini-powered, multilingual chatbot that answers complex budget questions in plain English, Hindi, or Telugu. Additionally, the platform uses machine learning to actively monitor public data and automatically flag suspicious activities like overspending or stalled projects. Ultimately, it turns dense, 500-page budget documents into clear, accessible insights to promote civic accountability.

Two-sided roadside assistance marketplace prototype (Flutter Web + FastAPI Backend)

An open-source, modular public transport routing engine built with Python 3.13+. It abstracts external transit APIs behind a resilient service layer to compute efficient multi-modal routes with integrated caching and strict compliance.

Scan any invoice or bill image — AI extracts the data, builds your financial dashboard. Fully offline. CPU only.

Interview Simulator

A real-time AI interview coach built with a Bun backend and Groq AI integration. This project includes:

browser-based job description and persona setup resume upload and text extraction for PDFs/DOCX/TXT live streamed interview assistant replies via SSE transcript export and review features frontend mic support and keyboard shortcuts

Use this file as the folder-level description for the project.

this is the project about health care

A Flask budget trip planner for affordable destination, hotel, transport, and itinerary recommendations.

OriginAI transforms research papers into startup opportunities, investor reports and pitch decks using AI.

Smart Road Maintenance & Monitoring System is a web-based platform that enables citizens to report road damages by uploading images and automatically capturing GPS locations. The system stores and tracks complaints, helping authorities identify, monitor, and resolve road issues efficiently. It aims to improve road safety, maintenance response time, and citizen engagement through technology.

Offline-first lecture transcription and structured study data extraction CLI/PWA.

FormForge AI is a smart form processing application that uses OCR and artificial intelligence to extract data from printed and handwritten forms and convert it into structured digital records for easier storage, search, and export.

Offline-first tribal health app

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.

Offline Medical Prescription Analyzer – Privacy-first offline OCR system using Tesseract for prescription extraction, validation, and CI/CD compliance automation.

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.

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

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.