Our project is an AI-powered educational app designed specifically for kids, where they can upload pictures of their homework and receive helpful suggestions on any mistakes in areas like grammar, spelling, and vocabulary. Initially, our goal was to create a tool that could analyze handwritten homework using Hugging Face models to provide targeted feedback, but implementing this proved challenging. Despite our best efforts, we encountered multiple obstacles in building this functionality, including issues with API validation and model limitations.

As a result, we shifted focus to develop a more streamlined MVP, which offers interactive exercises for kids to improve their English skills. Although this initial version includes fewer features, it sets a solid foundation for our original idea. Our vision for the future is to expand on this, integrating the full suite of features discussed in our presentation, such as detailed homework analysis through AI.

Despite deployment and integration challenges, we successfully brought our MVP to life, capturing the core of our concept and paving the way for future development. Our next steps are to resolve technical limitations and fully implement AI-driven feedback for uploaded homework images, ultimately making this app an engaging, supportive tool for young learners.

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