We developed an intelligent shopping application that addressed a specific challenge in e-commerce interfaces. Our solution innovated beyond traditional AI shopping assistants by focusing on natural conversation rather than command-based filtering.

The application was designed to understand context through conversation, allowing users to share their upcoming plans or trips while the system intelligently refined product recommendations based on these deeper insights. This approach solved the problem of users needing more personalized recommendations beyond what standard filters (size, color, gender) could provide.

Technically, we implemented real-time API integration with Footway's product database, structured non-volatile data into a knowledge base, and built semantic search capabilities powered by a large language model. The architecture enabled efficient product discovery through natural conversation.

Our solution was recognized among the top 4 projects at the hackathon, earning 3 jury points for its innovative approach to e-commerce interaction.

We addressed a common problem for youth-led boards: their dependency on adults' support to manage formal requirements. Many young people find these requirements tedious, difficult, or overwhelming, which can create an imbalance in power relations and reduce the sense of independence in their leadership.

We designed an AI tool that can act as a virtual "friend" guiding the youth through meetings. The tool includes features like agenda generation and minutes assistance tailored to board activities. This helps boards meet the specific formal standards required by state funders without adult involvement, reducing the risk of losing crucial funding and decreasing stress among young leaders.

Our solution aims to strengthen young people's participation in societal development by simplifying board formalities and increasing their understanding and application of democratic processes.