A full-stack, AI-enhanced application built to digitize and centralize the entire operational workflow for Balaji Health Care, a medical supply company. It manages inventory (with batch/expiry tracking), orders, and finances, replacing manual processes. The suite features an AI assistant (RAG) for data queries and AI-powered invoice scanning to automate order creation.

A Progressive Web Application that enables offline digital payments by bridging India's *99# USSD payment system with QR code scanning. The app eliminates internet dependency for UPI transactions, making digital payments accessible in low-connectivity areas. Features real-time offline QR detection using client-side processing, automatic UPI data parsing, and seamless USSD integration. Successfully deployed as an installable PWA with complete offline functionality after initial load.

An AI-powered web application that generates humorous, personalized roasts of Clash of Clans player bases. The tool fetches live player data by integrating with the Royal API proxy (bypassing official API IP restrictions) and uses Google's Gemini AI to analyze player statistics and optional base layout JSON. The project successfully launched to the r/ClashOfClans community, driving over 10,000+ views and significant user engagement.

An AI-powered summarization tool to analyze and simplify dense Terms & Conditions documents. The application uses Google's Gemini AI with few-shot prompting to parse legal text from PDFs or raw input, identify critical risks, and generate actionable advice. The tool is deployed as a public-facing Streamlit web app.

Developed a high-accuracy, fully offline, cross-platform multilingual translation application during an internship at the Defence Research and Development Organisation (DRDO). The system uses Meta's NLLB-200 model, achieving a BLEU score of 25.02 for Burmese-to-English, significantly outperforming Google Translate's baseline of 9.14. The application features a Python/FastAPI backend serving the Hugging Face model and a modern desktop UI built with React and Tauri.

A project to classify lung diseases (like Pneumonia and Lung Opacity) from Chest X-rays. The project benchmarked traditional ML pipelines (SIFT, HOG, LBP) against deep learning models, including ResNet50, DenseNet, and a custom ANN. The final custom model achieved 91.2% accuracy, incorporating SMOTE for class imbalance and LIME/SHAP for model explainability.