FarEye launches Foodeligent, an AI-based platform for the food delivery market

London, Dubai and New Delhi – 2 May 2018 - FarEye, a digital logistics platform, today launched Foodeligent, a ‘last mile’ SaaS-based delivery platform that uses machine learning and AI to enable restaurants offering food delivery companies to cut delivery times by up to 15%, and provide a far superior delivery experience.

Available immediately, FarEye Foodeligent has been designed to resolve the unique challenges facing the intensely competitive and fast growing food delivery market. Working to extremely tight delivery windows, and juggling high demand at peak periods (e.g. lunchtimes, evenings, weekends), restaurants and food delivery companies are judged by customers on how well they manage the overall delivery experience. FarEye’s Foodeligent AI platform for last mile logistics gives them the insight they need to: speed up deliveries; improve the customer proposition and experience; optimize operations; and reduce costs.

The platform uses machine learning to leverage a range of specific data points concerning order density and delivery time windows to improve delivery predictability. It also intelligently allocates orders to riders based on the time they are expected to be back at base. When fully integrated with last-mile logistics companies’ systems, Foodeligent enables the deployment of an elastic and scalable network that helps to reduce costs and is far more efficient at handling periods of peak demand.

System-based scoring of each delivery, as well as suggested improvement areas for individual delivery riders to help them become more efficient and make more deliveries in a given time frame, are also features of the new platform. Furthermore, an Uber-like tracking experience means that hungry customers can track their delivery on their mobile, while the real-time rating engine lets them give immediate feedback on the whole experience.

To help companies achieve a perfect delivery score from customers, the FarEye delivery platform dynamically calculates the estimated arrival time for each delivery taking into account variations in factors such as travel time, the day of the week & seasonality. It does this by collecting and storing data from eight key milestones during the entire delivery process (e.g. food handover time, drive to customer, courier to door, deliver and finish the transaction, and drive back to base), and applying AI & machine learning algorithms to this data to help identify and anticipate peak demand periods, expected delivery duration vs actual time taken, and the manpower required to cater to the expected demand.