Optimizing logistic fleets with machine learning to enable sustainable on-demand deliveries in cities
Two thirds of transportation take place in cities and is expected to grow dynamically over the coming years mainly due to e-commerce and an increasing demand for faster and more convenient deliveries. However, current methods to allocate deliveries among couriers and optimize them are slow, inefficient and often manual, leading to low utilization rates of vehicles and high costs. 
Airmee is an SaaS logistics platform that optimizes logistics fleets based on proprietary algorithms and consolidates by assigning the most suitable courier according to various parameters. We will use the SME funding to complete a Feasibility Study in Phase 1 to prepare for Phase 2 that will help us grow from our current TRL6 to reach TRL9.
Airmiz AB is a logistics startup founded by the entrepreneur Julian Lee (CEO) and the researcher at KTH in transport and logistics Adrian Prelipcean (CTO). The organization further consists of Fredrik Grahn (sales), Henrik Myhrvold (operations), Daniel Lee (operations), Daniele Tatasciore (front-end development), Tibor Fulup (front-end development) and Evgheni Gherghelejiu (mobile dev).
We license the Airmee platform to companies with their own logistics fleet and the fee per delivery. The total obtainable serviceable market is, at the moment, Sweden , where the e-commerce market is over €5B which corresponds to 50M deliveries valued at €250M.
Our competitors consist of optimization software that are limited in speed and flexibility, larger logistics providers that lack both the operations and technology to perform on-demand deliveries, and delivery startups that lack the technology to do the required optimizations. Airmee can optimize 500k deliveries (from different points within a city) per hour.
Airmee reduces congestion and pollution in cities by maximizing each courier’s capacity by enabling them to perform as many deliveries as possible per hour. Furthermore, it allows logistics providers to improve their margins.