Olympic MaaS

The main challenge of Milano–Cortina 2026 was, first and foremost, to provide digital services to very different audiences, each with distinct needs and expectations. On the one hand, for spectators, it was necessary to ensure a simple and immediate experience, with consistent, reliable, and real-time updated information, able to support travel between venues that are far apart as if they belonged to a single integrated system, across a multimodal offer that includes buses, trams, metro, shuttles and dedicated services, cars, and trains. On the other hand, for accredited users, in addition to the services described above, it was necessary to enable personalized features such as viewing dedicated transfer services and purchasing travel tickets.

This requirement was shaped by two major, closely interconnected layers of complexity. The first concerned the ecosystem: the Games required integrating, into a single platform, a variety of operators that differ significantly in service models, territorial coverage, and digital maturity, with the goal of ensuring a coherent experience across the entire Alpine macro-region involved. This heterogeneity was not only organizational, but also functional, because it meant bringing together different services and operational logics and making them interoperable with data and standards that were not always uniform, while preserving informational continuity and the quality of the user experience. The second crucial factor was time: the project had a compressed delivery window, with a start date tied to the opening of the Games and therefore effectively non-negotiable.

Further complicating the picture, the availability of “baseline” data was not sufficient: GTFS feeds for planned services alone often do not include essential elements for a complete experience, such as fares to correctly associate a price with the selected route, or shapes and metadata that help improve the quality and accuracy of journey planning. Moreover, in a high-pressure operational event, real-time information and service changes became decisive: disruptions, detours, and updates had to be communicated promptly and consistently across all channels, because any misalignment would immediately translate into impacts on the travel experience and, in turn, on the overall operations of the Games.

Based on the challenges described, OpenMove designed and implemented, and today delivers and maintains, the mobility management platform for the Milano–Cortina 2026 Olympics. The platform is built to collect, normalize, and enrich data, and then expose it through APIs; in this way, heterogeneous sources are transformed into a single, consistent, reusable information asset that can be leveraged by the different channels and systems involved. This API-first approach is part of OpenMove’s DNA and aligns with the API ecosystem we have long made available at api.openmove.com, designed to enable rapid integration, reuse, and strong governance of mobility data.

The work starts with the acquisition of datasets from operators and event-specific services. The system verifies their quality and consistency and harmonizes them into standard formats, managing GTFS for scheduled services and GTFS-RT for real-time information, as well as shapes and fare information (Fares files) to correctly match routes and prices and improve the journey-planning experience.

The project’s innovation lies not only in data integration, but in the ability to turn data into an industrialized digital service, delivered with reliability and performance standards suited to a global event.

OpenMove adopts a cloud-native, API-first architecture in which the central backend, OpenMove NUCLEUS, collects, normalizes, and enriches mobility information, exposing it securely and consistently to heterogeneous platforms and applications (see OpenMove’s API page – api.openmove.com). In this model, APIs become critical infrastructure: they are designed to guarantee uptime of up to 99.99%, sustain loads on the order of millions of users per day, and maintain fast, stable response times (under 800 ms) even during peak moments, both for data access and for latency-sensitive services such as the journey-planning algorithm and real-time information updates.

This robustness is complemented by a key element: interoperability speed, i.e., the ability to connect and operationalize third-party systems in a very short time. Thanks to connectors, standardized flows, and structured data-ingestion processes, new sources and new stakeholders can be integrated quickly, drastically reducing timelines and complexity compared to traditional projects.

The result is a backend system that does not simply “publish” data, but makes it reliable, measurable, and scalable, with monitoring and resilience mechanisms designed to ensure operational continuity, informational consistency, and a smooth user experience across the entire digital chain—from journey planning to integrations with third-party systems.