CitySwift

CitySwift is a public transport data intelligence and performance optimisation platform, purpose-built for bus networks to address the complexities and demands of modern urban mobility. Designed for operators and authorities managing fleets and routes of varying sizes, CitySwift merges deep domain knowledge with advanced data science to surface actionable insights, forecasts, and recommendations that drive measurable business outcomes and improved passenger experiences. Its core mission is to empower transport stakeholders to solve operational problems, optimise resources, and transition from intuition-led to fully data-driven decision making in network planning, service reliability, and financial performance. The foundation of the CitySwift platform is its proprietary engine that automates the collection, analysis, cleaning, and connection of raw bus network data. This engine ingests a broad spectrum of data sources, including timetable information, vehicle tracking, passenger flows, ticketing records, and traffic patterns. CitySwift then applies sophisticated algorithms to transform noisy, incomplete, or disparate raw data into a single, trusted source of truth. This unified dataset forms the backbone for generating insights into route performance, punctuality, occupancy, and origin-destination flows, among other critical metrics. What sets CitySwift apart is its holistic approach to data quality—automatically cleaning and enriching data to ensure reliability and trust in the analytics delivered through its dashboards and reporting tools. The platform provides a suite of features tailored for bus operators, authorities, and planners. With CitySwift, users can rapidly identify opportunities and trends in their networks, build transparency across teams, and accelerate collaborative data-led decision making. The platform’s intuitive dashboards and customisable reports allow stakeholders to monitor service health, review passenger demand, and track route profitability in real time. Advanced origin-destination algorithms unlock meaningful patterns in passenger boarding and alighting, enabling more informed service reviews, frequency adjustments, and resource reallocations. CitySwift’s demand-based frequency and demand forecasting tools are particularly valuable in responding to shifting mobility needs and market conditions, helping networks adapt resources proactively to meet passenger expectations and achieve commercial objectives.