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Mobile Application for Bike Routes

BCNByBike is a app that utilizes AI to guide cyclists in Barcelona along the most efficient and safe bike routes. The app offers a seamless user experience, enabling cyclists to find, save, and share their preferred routes. It combines advanced mapping technology, an intuitive interface, and innovative AI algorithms to provide predictive and personalized route suggestions.




Services Used

Development - Research - UX/UI Design - Dedicated Team


The primary challenge in developing BCNByBike was to create an intuitive and engaging application that delivered accurate, personalized, and predictive route information while maintaining visual appeal. Our development team harnessed the power of technologies such as Mapbox SDK, React Native, Ruby on Rails, and cutting-edge AI models to create an incredibly functional and visually engaging application. The custom algorithm, empowered by machine learning, ensures optimal routes are suggested based on user preferences and historical data, making cycling more enjoyable than ever.

Design & Development

To find the quiet streets that make cycling a joy.

Machine learning

Our team incorporated advanced mapping technology, a custom AI-enhanced algorithm, and machine learning models. This approach allowed users to discover the most efficient and safest cycling routes in Barcelona while also suggesting new routes based on historical patterns and preferences. The UI has been designed meticulously, ensuring a clean, modern, and easy-to-navigate experience.


To support the app's functionality and scalability, we employed AWS for data storage and real-time updates. Additionally, AWS Lambda and Amazon SNS were used for real-time updates on traffic, road closures, and other relevant information, providing users with up-to-the-minute and accurate route details.

Project Scope

AI-Powered Customized Route Planning

Optimized routes considering user’s location, historical data, travel time, public notifications, and other road conditions are suggested, thanks to our AI-enhanced algorithm developed with Ruby on Rails.

Real-time Updates

We implemented AWS Lambda and Amazon SNS to enable real-time updates and push notifications, keeping users informed with the most up-to-date and accurate route information.

Social Sharing

By leveraging native sharing capabilities provided by React Native, we integrated social media platforms and facilitated route sharing through email and direct messaging within the app.

Performance Tracking

We built an offline mode that allows users to access certain data at any time, from anywhere.

User Profiles

Ruby on Rails and Amazon Cognito are used to enable users to create and customize their profiles, with the AI learning and adapting to individual user preferences over time, making the experience increasingly personalized.

Custom Route Optimization

In order to find the best and safest routes for users depending on their input and current conditions, we developed an internal algorithm in Ruby on Rails.

Enhanced UI/UX Design

Our team skillfully designed a visually appealing and user-friendly interface with both light and dark themes, ensuring compatibility across a wide range of devices and demonstrating our expertise in User Interface (UI) design.

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