Beyond the Booking — Dynamic Intent-Aware Personalization in Smart Cities

The problem:

AI travel assistants and airline booking engines struggle to distinguish between a traveler’s permanent profile and their current trip intent. This creates a generic, sometimes annoying, customer experience. 

Airlines have the opportunity to extend their relationship with travelers beyond the flight experience and remain connected throughout the destination journey. At the same time, destination cities such as Barcelona face the challenge of better understanding and guiding tourist flows, promoting local and sustainable commerce, and coordinating last-mile green mobility options for arriving passengers. 

Challenge statement:

How can we use privacy-first open city data (such as urban mobility networks, cultural events calendars, and municipal APIs) to dynamically predict a traveler’s current journey intent, allowing Vueling to deliver hyper-personalized, context-aware services without causing over-personalization friction?" 

What are we looking for

We invite startups, software developers, and research centers specializing in Responsible AI, Data Science, and Edge Computing to propose solutions in the following areas: 

• Intent Prediction Engines: Lightweight, privacy-by-design algorithms that can cross-reference minimal user inputs with city-level real-time data to identify if a trip is for business, leisure, or a hybrid "bleisure" stay. 

• Smart City Data Integration (Barcelona API Bridge): Solutions that integrate Vueling's app with Barcelona’s public data ecosystems (e.g., TMB transit data, Bicing shared bikes, local festival schedules, or Fira Barcelona congress calendars) to offer personalized last-mile transit and local experiences. 

• Contextual "Invisible Retailing": AI interfaces that dynamically adjust the services suggested to the user during their flight and upon arrival in Barcelona (e.g., suggesting a quiet workspace versus a family-friendly transport option).