Case studies

The client is a mid-sized restaurant chain with about 1200 locations in over 30 countries. Each restaurant provides full-service dining, where waiters take orders, serve food and manage table turnover. Most locations have two dining areas, which can make it hard for staff to keep track of all tables. The client wanted to improve AI for restaurant management by reducing wait times, speeding up table cleaning, and helping staff respond more quickly. Their goal was to use real-time table monitoring and smart video analytics to support better decision-making and improve the overall customer experience, showing how to track table status and wait times using AI in restaurants.

A major cosmetics and beauty retailer runs a high-volume warehouse that processes thousands of online and in-store orders daily. Customers place orders through the website or mobile app, triggering an automated fulfillment process. Warehouse staff pick items from inventory, scan barcodes to verify them, and pack them into labeled boxes. These boxes are then sorted at the delivery zones and assigned to couriers for scheduled deliveries. The warehouse uses barcode scanning, inventory management systems and automated package tracking system to monitor order accuracy, worker efficiency, and box movement. Since orders must be processed within strict time limits, the warehouse continuously optimizes the storage layout, packing stations planning, and workflows to improve efficacy and reduce errors.

Nowadays we see the importance of new digital tech in changing how the world trades. These modern tools are giving traders a big leg up, helping them deal with and succeed in a world that's getting more complicated to do business in. Our client requested us to create an actionable AI-backed tool that would analyze traders’ behavior on the market with high operational efficiency and prediction accuracy. Read on to discover more about the project.