GlobeWIAL

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Inspiration

We were inspired by the complexity of how World Institute for Action Learning operates across multiple countries and chapters. Each chapter works independently, but there’s still a need for global consistency and connection. We noticed how hard it is for clients to find the right coach across regions and languages. That gap between global reach and local accessibility became the main motivation for GlobeWIAL.

What it does

GlobeWIAL is a global platform that connects clients, coaches, and chapter admins in one place. It allows users to search for coaches using multilingual AI, explore availability through an interactive world map, and manage chapter operations. Different roles (admin, coach, client, etc.) get customized dashboards tailored to their needs. Overall, it simplifies discovery, management, and collaboration across countries.

How we built it

The project was developed using a modular web architecture with HTML, CSS, and JavaScript. The UI was designed to be role-based, where different users have different dashboards. AI-powered semantic search was used to connect coaches with clients regardless of their language. Other features, including an interactive world map, chat assistant, and analytics dashboard, were developed using custom frontend logic.

Challenges we ran into

One of the biggest challenges was handling multilingual search in a meaningful way. Mapping different languages to the same intent without using external APIs required careful design. Another challenge was managing the complexity of multiple user roles and keeping the UI clean. We also had to ensure the platform felt scalable while still being a prototype.

Accomplishments that we're proud of

We’re proud of creating a fully functional end-to-end platform instead of just a basic prototype. The AI-based coach matching and global map visualization stand out as strong features. We also successfully handled multiple user roles with different workflows in one system. Overall, we built something that feels close to a real-world product.

What we learned

We learned how to design systems that balance global scalability with local customization. Working on role-based dashboards helped us understand real-world product design challenges. We also explored how AI can improve user experience, even with simple logic. Most importantly, we learned how to structure and present a complex project clearly.