In urban areas, there is continuous movement of people in large numbers, however the allocation of urban resources is essentially static that leads to unnecessary operational and capital expenditures for service providers and lower levels of service for end users as resources go unused or fail to effectively be reallocated to meet unanticipated demand peaks. EINO’s predictive software product accurately forecasts the movement of people and their intent. EINO empowers its customers to optimize resources as efficiently as possible because its ever-updating, carefully curated data pool provides accurate, contextual actionable insights into future demand. These insights empower users to 1) identify and anticipate temporal and spatial congestions, and under-utilization, 2) understand the factors that will cause the congestions, and 3) pinpoint future opportunities for optimization based on this information. EINO’s service is currently tailored for ride-hailing and network connectivity sectors and is soon expanding to supply/chain logistics, emergency services, and public safety.
EINO is a team of Cornell and Columbia information scientists who are passionate about smart cities and data-driven ecosystem. With deep industry and entrepreneurial experience and world-class technical skills, EINO aims to develop and market a product that will be a game changer for the optimization of key resources in urban centers around the globe.
EINO is part of Cornell-Tech Runway Program.