quick-commerce

End-to-end analytics suite for Blinkit, Swiggy, and JioMart — 100k+ orders analyzed to forecast demand, optimize SLAs, and reduce churn (+37% growth impact)

Android-first Compose Multiplatform quick-commerce demo with an offline catalog, persistent crate, transparent pricing, deterministic checkout recovery, and Room-backed orders.

Quick-commerce delivers in 10 minutes. But the customer spends 15 minutes deciding what to order. The bottleneck isn't the rider — it's the shopping itself.

IIM SMF 2026 Research Proposal & Empirical Literature Base | Q-Commerce Unit Economics & Last-Mile Logistics in India

🛒 A production-grade 10-minute grocery delivery platform. Features a Next.js monorepo powering Customer, Admin, and Delivery apps with real-time Socket.io tracking.

Score your quick commerce cities by ad performance. Know where to scale, hold, or cut budget.

AI-powered quick commerce intelligence system that tracks products, pricing, and availability across Blinkit, Zepto, and Instamart.

A full-featured quick commerce application built as a monorepo with Nuxt 3, NestJS, and PostgreSQL. Delivers groceries in minutes with real-time order tracking, multi-role access, and a complete admin dashboard.

Quick-commerce fashion platform delivering clothing to customers in 30 minutes. Built with React, Node.js, Express, and MongoDB.

Platform connecting local shops for ultra fast cheap delivery... Created at https://coslynx.com

Business analytics & data visualization project analyzing Blinkit’s quick commerce model-delivery speed, urgency marketing, customer behavior, and revenue insights using Tableau.

End-to-end supply chain analytics warehouse modeled in PostgreSQL (Star Schema) and Power BI tracking dark-store stockouts and vendor OTIF SLA adherence.

Consumer-side grocery price intelligence and cart optimization platform.

This is the server side code for a real life quick commerce application clone

Analysis of Blinkit's public filings, quarterly growth, store economics and mature-store returns, with Python and Excel.

End-to-end quick commerce analytics project leveraging Excel, SQL, Python, and Power BI for sales analysis, customer insights, and business performance monitoring.

AI-powered system for optimizing inventory, demand forecasting, and supply chain in quick commerce dark stores

SQL and Power BI analysis of customer behavior, product performance, revenue trends, and delivery operations.

🏗️ System architecture study comparing e-commerce vs quick-commerce — focusing on backend architecture, data consistency, scalability, and operational complexity.