URBANITE

Asistobe addresses the challenges of inefficient public transport systems caused by only relying on slow and expensive data sources like surveys and interviews when gathering information about people’s mobility habits. Urban mobility today demands dynamic solutions to tackle overcrowded buses, delayed trams, and rising environmental concerns. This project provides cities, municipalities, and public transport operators with actionable, data-driven insights into current and future transport demand.

Inspired by the need for smarter, more sustainable urban mobility, Asistobe integrates artificial intelligence and machine learning to analyse historical, GPS, mobile network and passenger data. This enables precise modelling of real passenger movements across multimodal transport systems, including buses, trams, trains, and bicycles. The main objective is to empower public transport authorities (PTA) and operators (PTO) to optimise operations, plan for future demand, and create more sustainable, safer cities.

The SaaS platform’s user-friendly interface offers automated predictions with an 85-90% accuracy rate, near real-time movement tracking and scenario modelling capabilities. By reducing costs and enhancing ridership, Asistobe simplifies complex decisions and fosters efficient public transport systems.

Developed with urban planners and transport operators in mind, Asistobe’s solutions are particularly tailored for small and medium-sized cities (<500k inhabitants) with limited resources for advanced data analysis. Piloted in 2025, it partners with local consultancies to navigate regulatory barriers and accelerate adoption.