Passenger-facing tools: Mobile Apps

At Swiftly, agencies that purchase Transitime will have multiple options to display these predictions on mobile apps. Swiftly will help provide real-time predictions into your selected third-party apps.

Google Maps

Depending on the agency, Google Maps integrations will be managed either one of two ways: 

1. Your agency manages the integration. Google prefers that the agencies manage the predictions data themselves.
2. If your agency works with Trillium, there are cases where Trillium will integrate into Google Maps for your agency. Trillium has a long-standing relationship with Google, and Google has made the exception to work with Trillium. Please keep in mind that this is a paid service from Trillium. If you would like to pay for this service please contact your Customer Success Manager or [e-mail].

Google integration starts early within an agency’s implementation, this process typically takes 6-8 weeks to complete.

Transit App

Swiftly works closely with Transit app to integrate passenger information. Transit routinely integrates GTFS data coming from Real-Time Passenger Predictions and Rider Alerts tools for any agency. Transit app further shows detour information entered in Service Adjustments for agency Royale partners. In all cases, Swiftly and Transit coordinate directly on troubleshooting any issues that arise. For more information, see the Transit website.

Agency or Third-Party Apps

Many agencies want predictions and/or vehicle locations displayed on their own agency app or other third-party apps (besides Transit and Google). At Swiftly, we believe that your data is your data. Through open APIs, our data predictions information is flexible and open for any interface you want to offer your passengers. 

When integrating Swiftly predictions into your agency's website or other third-party web interfaces, Swiftly will offer all the necessary API access and optional Swiftly API training. It is up to the agency or developer to utilize the API to push vehicle position and predictions to those interfaces.