AIoT Voice Picking System

As Verde Local rapidly expanded its retail footprint to 83 stores and a growing catalog of over 9,000 SKUs, its warehouse operations struggled to keep pace. Distribution center employees were spending excessive time manually picking goods for delivery services and retail partners, leading to bottlenecks, increased error rates, and inefficiencies. Traditional warehouse management systems lacked real-time adaptability and failed to optimize picker routes, resulting in wasted labor hours and delayed shipments. To maintain high service levels while scaling operations, Verde Local needed a smarter, voice-guided system that could streamline workflows, reduce errors, and boost picker productivity.

To address the inefficiencies in its warehouse operations, Verde Local partnered with a Plavno custom software development company to implement an AIoT-based voice system tailored to its logistics environment. The solution integrated artificial intelligence, IoT sensors, and voice recognition technology to create a hands-free, real-time guidance system for warehouse staff.



The AIoT voice system delivered dynamic voice instructions to order pickers, optimizing their routes based on live inventory data, order priorities, and warehouse layout. By leveraging deep learning algorithms, the system continuously analyzed picker performance and warehouse flow, adapting instructions to minimize travel time and reduce picking errors.




The warehouse manager begins by generating the order composition and uploading it into the company’s accounting system—either a Warehouse Management System (WMS) or Enterprise Resource Planning (ERP) platform. The system then converts the order into a series of detailed, step-by-step instructions, specifying exactly which section, rack, and shelf to access, along with the quantity of items to pick.

These instructions are transmitted to a mobile voice terminal worn on the picker’s belt. The device delivers synthesized voice commands, guiding the employee through each step of the process. As the picker completes each task, they confirm it verbally through the microphone. Once acknowledged, the system immediately issues the next instruction. This loop continues until the entire order is fulfilled, creating a hands-free, highly efficient workflow.



IoT-enabled devices tracked picker movements and inventory levels, feeding data into a central analytics engine. This allowed warehouse managers to monitor operations in real time, identify bottlenecks, and make data-driven adjustments. The system also integrated seamlessly with Verde Local’s existing merchandise management software, ensuring smooth coordination between demand forecasting, inventory, and order fulfillment processes.



Voice technology enables end-to-end, real-time management of warehouse operations—from receiving to shipping. It supports the picking of both unit-based and weight-based goods, and allows large orders to be assembled simultaneously by multiple pickers without confusion or delay. The system also includes automated weight verification for completed pallets, ensuring accuracy and compliance. Additionally, it streamlines operations by automatically assigning picking tasks and generating pallet labels, reducing manual intervention and boosting overall efficiency.