Google GTM Portal

Feb 2026 → Apr 2026

A unified catalog platform built for Google Cloud Next 2026 event, consolidating TCS's AI offerings into a single, searchable surface so that the right solution could be found before the conference badge had time to cool.

Agentic AMS Platform

Feb 2025 → Jan 2026

An autonomous multi-agent system that detects, diagnoses, and resolves production incidents end-to-end, with a human kept firmly in the loop and a vector-indexed brain consulted at every step.

Mar 2026 → Mar 2026

A reference implementation of the AG-UI protocol a chat interface whose purpose is not merely to respond, but to make the ordinarily invisible machinery of agent communication legible.

Sept 2025 → Apr 2026

A Python library for Vedic astrology calculations, publishing to PyPI the ancient machinery of Jyotish: divisional charts, dasha timelines, and yoga combinations, all computable from a birth moment and a coordinate.

Jul 2024 → Sept 2024

A modern, responsive e-commerce web application built using Next.js, Tailwind CSS, and Supabase. The project features dynamic product listing, a fully functional shopping cart, and a clean, mobile-friendly interface and a order and inventory management system for the admin to access the store.

Sept 2023 → May 2024

Lung cancer kills with particular efficiency partly because it so often goes unnoticed until it has made itself unmissable. This project assembles three deep learning architectures, V-Net, YOLOv5s, and DETR, into a single detection pipeline that finds the nodules a radiologist might miss and declines to invent the ones that are not there.

Sept 2023 → Dec 2023

Lense is an Android application for selling pre-owned products with AI-powered value estimation. It simplifies listing items by automatically generating descriptions and estimating product value using image classification and captioning models.

Oct 2022 → Jan 2023

Parkinson's disease leaves a signature in the voice long before it announces itself in more obvious ways. This project asks whether that signature, extracted as biomedical acoustic features from a voice recording, is legible to a machine learning classifier, and then asks the question of nine different classifiers simultaneously to find out which one reads it best.