Use big data and machine learning to increase transit network performance


The transit data engine

Visualize and report key metrics; accurately predict vehicle capacity and journey times; and optimize your timetables

CitySwift is a cloud-native, specialist data engine for mass transit networks.

Operational information is combined with a vast array of big data sources to develop rich datasets that are unique to each transit network and location. Machine learning models are trained on this data to deliver highly accurate predictions.

The CitySwift transit data engine currently powers three products: SwiftMetrics delivers network analysis at scale; SwiftSchedule rapidly generates optimized timetables; and SwiftConnect enables the sharing of accurate vehicle capacity predictions on a stop-by-stop basis, helping passengers make the right journey choices.



Transit network analysis at scale

Fully understand and improve the performance of your mass transit network. SwiftMetrics seamlessly integrates with your existing technology systems to instantly visualize and automatically report detailed performance, efficiency and ridership metrics – enabling informed decision-making for network development and growth.

  • Instantly visualize detailed performance, efficiency and ridership metrics
  • Track and report network performance and KPIs
  • Review historical data with deep-dive insights
  • Analyze mobility patterns to predict future trends and opportunities
  • Create, customize and share visually-rich dashboards
  • Export information in a variety of formats
  • Augment and integrate with your existing technology infrastructure


Rapid bus timetable optimization

Create enhanced timetables that balance vehicle supply with passenger demand. SwiftSchedule seamlessly integrates with your existing network planning systems to accurately predict journey times based on operating conditions and ridership levels, significantly reducing network review timescales and increasing network efficiency.

  • Accurately predict journey times and passenger demand
  • Rapidly generate new, optimized timetables
  • Analyze and improve the performance of existing timetables
  • Customize schedules with route and stop constraints
  • Model multiple future scenarios
  • Share timeband information with scheduling software
  • Integrate with existing network planning tools


Accurate bus capacity predictions

Spread demand peaks and improve the comfort and safety of bus users. SwiftConnect seamlessly integrates with your existing technology systems and uses AI to predict capacity levels for every vehicle, for any specific date and time. Information is continually updated based on actual ridership, and shared with passengers in an easy-to-understand ‘traffic light’ format.

  • Predict capacity levels for every bus, at every stop, at any time
  • Get accurate predictions up to two weeks in advance
  • Share information with transit users to aid their journey planning
  • Use predictions to inform short-term network planning during uncertain times
  • Reduce the risk of human error from driver or crowdsourced passenger counts
  • Update product name and appearance to fit your brand identity
  • Integrate with your existing technology infrastructure