Nadisaa Meats

The Problem

Managing perishable inventory is exponentially harder than regular e-commerce. Nadisaa needed real-time stock tracking, predictive ordering, temperature-controlled logistics, and precise delivery scheduling—all while minimizing food waste.

Research & Discovery

We embedded with the Nadisaa operations team to understand their workflow. Key insight: inventory forecasting needed to account for seasonal demand, local events, and weather patterns that affect meat consumption.

Design Approach

An operations dashboard that gives real-time visibility into inventory levels, delivery routes, and temperature logs. The customer-facing app focuses on delivery slot selection and real-time order tracking.

Architecture

React admin dashboard and customer PWA, Node.js microservices, PostgreSQL for transactional data, Redis for real-time inventory caching, Docker for containerization, and AWS for scalable infrastructure.

Engineering

We built a predictive ordering algorithm using historical sales data, integrated with temperature sensors via IoT APIs, and implemented route optimization for delivery logistics. The system sends automated alerts for low stock and temperature anomalies.

Technology Stack