SproutSense

Inspiration

We were inspired by how often early neurodevelopmental disorders go unnoticed until children begin to struggle in school. Early signs of ADHD, dyslexia, or speech and motor delays appear between ages three and six, but diagnosis usually happens much later after academic or emotional setbacks. We wanted to change that by creating a system that uses the data schools already collect to identify early learning difficulties and help children reach their potential.

What it does

SproutSense is an AI powered web platform that analyzes school exam data, teacher feedback, and behavioural patterns to detect early learning disabilities in children aged three to nine and to predict ideal career paths for students aged eleven to seventeen.

It produces two main reports:

1. Cognitive and Mental Health Report — identifies potential signs of learning disorders.
2. Career and Skillset Report — highlights each student’s strengths, weaknesses, and best suited learning paths.

How we built it

We built SproutSense using Next.js for the frontend, Flask for the backend, and TensorFlow for AI analysis. The system processes both teacher observations and student exam data to identify key features such as reasoning ability, language fluency, consistency, and problem solving approaches. The results are displayed through interactive dashboards and can be exported as reports for teachers, parents, and students.

Challenges we ran into

It was difficult to collect structured and consistent data for young children, so we designed simplified teacher observation forms. Building one platform that could handle both healthcare detection and educational career mapping was another major challenge, as it required careful data design and validation. We also had to ensure responsible handling of sensitive information while maintaining accuracy and interpretability in the results.

What we learned

We learned that combining artificial intelligence, education, and psychology can create meaningful and socially impactful solutions. Working on SproutSense also taught us the importance of designing ethical and inclusive systems, especially when dealing with children’s cognitive and personal data.

What’s next

Next, we plan to test SproutSense in partnership with schools to improve prediction accuracy using real longitudinal data. We also want to expand the system to include adaptive teaching strategies, personalized career guidance, and detailed resource recommendations so that SproutSense can become a complete learning and growth companion for students, parents, and teachers.

Built With

• ai
• api
• clerk-for-auth
• convex-for-database/backend
• framer-motion-for-animations
• next.js-16-with-react-19-and-typescript
• resend-for-email
• tailwind-css-with-shadcn/ui-components
• three.js-with-react-three-fiber-for-3d-shader-effects