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 sophisticated multi-agent system where a Knowledge Base Agent actively queries, stores, and learns from its own trading decisions via RAG. Implements agentic RAG with pre-query retrieval and post-decision learning loops that enable continuous improvement. Features a 6-agent collaborative pipeline with Bull vs Bear debate researchers, Risk Manager, and Final Trader.

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.

A WhatsApp chat analyzer that transforms exported chat data into detailed year recaps with AI-generated insights. Processes up to 15,000 messages using Google's Gemini AI to generate personalized analysis including inside jokes, emotional highlights, trending topics, and humorous participant roasts. Features interactive dashboards with charts, word clouds, and timeline graphs.

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.

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.

A deep learning application for automated waste segregation, classifying images into Biodegradable and Non-Biodegradable categories with 98.86% accuracy. Built using FastAI and PyTorch with a ResNet18 backbone, utilizing progressive resizing and augmentation for robust performance. It outperforms a custom VGG16 baseline and offers a real-time web interface via Streamlit.