Predictiv AI subsidiary agrees to master agreement with Metrolinx for on-demand transit software

The agreement enables eligible transit agencies to access Shift's platform and related services through separate purchase agreements.

Predictiv AI Inc. (Predictiv AI) subsidiary, Shift Technologies Canada Inc. (Shift), has entered into a master agreement with Metrolinx for the supply and delivery of on-demand transit software and related services. The agreement took effect Oct. 26, 2026, for an initial one-year term, with four additional one-year extension options. 

Predictiv AI notes Metrolinx's TPI program currently includes 43 active transit agency partners across Ontario, providing a broad procurement network for municipal transit solutions. The agreement enables eligible transit agencies to access Shift's platform and related services through separate purchase agreements, creating opportunities for adoption across Ontario's public transit network. 

According to Predictiv AI, the agreement creates an opportunity for Shift to expand its presence in Ontario's municipal transportation market through a common procurement framework. Shift intends to pursue potential software subscription, implementation and support opportunities with eligible transit agencies that elect to procure services under the framework. 

The company's objective is to help municipal transit operators deploy flexible, technology-enabled services suited to local community needs. Predictiv AI says the agreement represents a platform for pursuing long-term municipal customer relationships and growing its Canadian public transit software business. 

"This agreement represents an important milestone for Predictiv AI and our commitment to building Canadian technology for Canadian communities," said Predictiv AI CEO Suman Pushparajah. "Public transportation is entering a new era where intelligent software, real-time data and more flexible service models can help municipalities respond to the needs of their residents. The master agreement provides a framework through which eligible Ontario transit agencies may elect to procure our technology. We look forward to pursuing those opportunities and continuing to develop our transportation software business."  

On-demand transit allows riders to request trips through digital and assisted booking channels while transit agencies coordinate vehicles, routes and pickups according to local operating requirements. Depending on the service model chosen by each agency, the technology can support accessible door-to-door trips, demand-responsive service areas, fixed-route operations and first-mile/last-mile connections to wider transit networks. 

Shift's cloud-based platform is designed to support passenger booking, automated dispatch, dynamic route optimization, operator applications, real-time fleet visibility, operational reporting and related implementation, training and technical support. By linking rider demand with routing and operational data, Predictiv AI says the platform is intended to help transit teams adapt services to changing community needs and align vehicles and routes with passenger demand while giving operators clearer information to manage day-to-day service. 

"Every municipality has different transportation needs, from accessible door-to-door service to connecting smaller communities with larger transit networks", said Predictiv AI COO Sana Srithas. "Our approach is to give transit operators a flexible platform that can be configured around their specific needs while providing the visibility, tools and operational support required to deliver reliable service." 

About the Author

Brandon Lewis

Brandon Lewis

Associate Editor

Brandon Lewis is a recent graduate of Kent State University with a bachelor’s degree in journalism. Lewis is a former freelance editorial assistant at Vehicle Service Pros in Endeavor Business Media’s Vehicle Repair Group. Lewis brings his knowledge of web managing, copyediting and SEO practices to Mass Transit magazine as an associate editor. He is also a co-host of the Infrastructure Technology Podcast.

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