The problem Dyslexis solves

The Dyslexis website addresses the unique challenges faced by individuals with dyslexia, a learning disorder that makes reading, writing, and recognizing letters and colors difficult. Dyslexia affects 10-15% of young learners globally, impacting their ability to keep pace in traditional educational settings. Common struggles include distinguishing similar letters (like "b," "d," "p," and "q"), organizing thoughts, and reading fluently. These difficulties often lead to frustration, lower confidence, and a lack of accessible resources for tailored learning.

Dyslexis aims to solve these issues by providing a supportive, inclusive platform specifically designed for dyslexic individuals. The site offers a range of personalized tools and resources, including interactive games to strengthen letter and color recognition, AI-powered handwriting analysis for early dyslexia detection, and an educational resource hub for dyslexia-friendly learning materials. Additionally, the site connects users with a directory of therapists and specialized schools, providing easy access to expert support.

By addressing these core challenges, Dyslexis empowers dyslexic learners to build essential skills, boosts their confidence, and supports educators and families in creating an environment where every learner can thrive.

Challenges we ran into

Understanding Dyslexia Needs: Crafting tools specifically beneficial for dyslexic individuals required extensive research and consultation with experts to ensure we addressed real learning challenges. Understanding the nuances of how dyslexia affects reading, writing, and color recognition took time and adjustment.
Handling Large Image Database: Managing a database with over 200,000 images used for handwriting analysis and training the AI prediction tool presented technical challenges.
Handwriting Analysis Accuracy: Developing an AI-based handwriting prediction tool involved complex algorithm development. Ensuring accuracy in detecting dyslexic tendencies through handwriting required refining the model and gathering diverse data to improve prediction reliability.