Description
🖼️ Tool Name:
CitySwift
🔖 Tool Category:
AI-powered public-transport performance optimisation platform; it falls under the category of analytics & forecasting tools that enable transportation operators and authorities to optimise bus networks and service delivery.
✏️ What does this tool offer?
CitySwift provides a performance optimisation platform for bus networks and public transit operators. Key offerings include:
A data-engine that ingests, cleans, enriches and analyses raw bus-network data (vehicle location pings, schedule data, demand data, boarding/alighting) to deliver actionable insights.
Demand forecasting and origin-destination intelligence: the system uses AI and ML to predict passenger flows, occupancy and service demand, enabling operators to adjust frequency and resources.
Business-intelligence dashboards and recommendations for network optimisation: route adjustments, scheduling enhancements, performance metrics (punctuality, reliability), cost savings and resource allocation.
Automated data-processing pipelines and quality monitoring: the platform automates ingestion and cleaning of large volumes of transport data, reducing manual work and increasing data confidence.
⭐ What does the tool actually deliver based on user experience?
• Serves networks handling billions of passenger journeys annually and processing huge volumes of bus-location and demand data.
• Case example: The operator Go‑Ahead Group used the platform and reported improvement in service punctuality by up to ~14% and increase in customer journeys by ~4% in certain divisions.
• Enables transport operators and authorities to shift from reactive maintenance/planning to data-driven, proactive decision-making for network performance, cost-efficiency and customer experience.
🤖 Does it include automation?
Yes — CitySwift incorporates several automated and AI-driven workflows:
• Automated ingestion and cleaning of raw data from multiple sources (vehicle GPS, schedule, demand, geography).
• Automated analysis and enrichment (for example inferring demand when data is incomplete, using geospatial and statistical models) so that insights can be generated even from imperfect data.
• AI/ML-based forecasting and recommendations: predicting demand, occupancy, performing “what-if” simulations, enabling operators to simulate changes in service and resource allocation.
💰 Pricing Model:
Enterprise / B2B model: CitySwift is targeted at transit operators, authorities and large bus-networks. It does not advertise simple consumer-pricing tiers publicly.
🆓 Free Plan Details:
No publicly described free tier for end-users; the solution is an enterprise-grade mobility platform.
💳 Paid Plan Details:
Paid engagement typically involves licensing of the platform, integration of data sources, onboarding, support, and ongoing analytics services. Specific pricing depends on network size, data volume, region and service level.
🧭 Access Method:
• Via the web platform of CitySwift:
• Integration with transit operator’s data systems (vehicle tracking, boarding systems, schedule data) and dashboards for operations teams.
• Typically requires enterprise implementation with data-team, training, and consultancy.
🔗 Experience Link: