Grozo: An Ai-powered Online Grocery Delivery System

Abstract

Widespread Smartphone Adoption And Ubiquitous High-speed Connectivity Have Collectively Reshaped How Consumers Discover And Purchase Goods, Driving Sustained Migration Toward Digital Retail Channels Across All Product Categories. The Grocery Segment, Long Anchored To In-person Shopping, Is Now Experiencing Accelerating Structural Change As Customers Increasingly Prioritise Doorstep Delivery, Broad Product Assortment, And Faster Fulfilment Over The Traditional In-store Experience. This Paper Presents Grozo, A Production-ready, AI-powered Online Grocery Delivery Platform Built On The MERN (MongoDB, Express.js, React, Node.js) Technology Stack. Grozo Integrates A Suite Of Intelligent Subsystems — Including A Multi-signal Product Recommendation Engine, A Real-time Dynamic Pricing Model, An Inventory Forecasting Module, A Haversine-based Route Optimisation Algorithm, And A Gemini-powered Conversational AI Chatbot — To Deliver A Seamless And Personalised Shopping Experience. The System Supports Over 8,000 Product Listings Sourced From BigBasket, Multi-modal Payment Processing Via Razorpay, Live Order Tracking Through Leaflet.js/OpenStreetMap, A Four-tier Loyalty Rewards Programme, And A Voice-command Interface Built On The Web Speech API. Experimental Evaluation Demonstrates That Grozo Achieves Sub-second API Response Times, A Recommendation Click-through Rate Improvement Of 34% Over Static Listings, And A Dynamic Pricing Engine Accuracy Within 8% Of Market Fluctuations. The Architecture Described Herein Offers A Scalable Blueprint For Next-generation AI-driven Grocery Retail Platforms.

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