DyslexiCore

Inspiration

DyslexiCore was inspired by the growing need for accessible, engaging, and early cognitive screening tools for children with learning difficulties such as dyslexia. Traditional screening methods are often expensive, stressful, inaccessible, or heavily dependent on specialist availability. We wanted to create a platform that feels less like a medical assessment and more like an interactive adventure.

We were also inspired by the idea of combining AI agents, adaptive learning systems, and gamification to create a futuristic educational healthcare platform that can personalize screening experiences in real time.

The goal was to build something emotionally supportive, visually immersive, and technologically innovative — a system where AI actively collaborates to understand how a child learns.

What it does

DyslexiCore is an AI-powered cognitive screening platform designed for children aged 4–9. It uses space-themed mini-games, adaptive gameplay systems, and multi-agent AI analysis to detect patterns associated with dyslexia and other reading-related learning difficulties.

The platform includes:

Interactive cognitive missions such as: Star Tracker Phoneme Popper Letter Mirror Reverse Recall Rapid Flash Words CVC Explorer Real-time telemetry analysis: response times hesitation tracking reversal detection attention stability decoding confidence Autonomous Jac AI agents including: Observation Agent Risk Analysis Agent Adaptive Learning Agent Companion AI Agent Psychometric Agent Intervention Planning Agent A dynamic AI Companion called COSMO that provides contextual guidance and emotional encouragement during gameplay. A Parent & Teacher Dashboard that visualizes: dyslexia risk indicators cognitive analytics reading patterns fatigue curves personalized intervention recommendations

The system adapts difficulty in real time based on child behavior and generates AI-assisted learning insights.

How we built it

We built DyslexiCore using a modular frontend architecture combined with simulated Jac-inspired agentic AI systems.

Frontend:

React.js Vite Tailwind CSS Framer-motion style animations Glassmorphism and neon UI styling

AI Architecture: We designed a multi-agent system inspired by Jac autonomous agents.

The platform contains simulated AI modules such as:

Dynamic Stress Adjuster Agent Companion Co-Pilot Agent Phonological Analysis Agent Visual-Spatial Agent Psychometric Agent Intervention Planner Agent Mission Routing Agent

These agents collaboratively process telemetry generated from cognitive games and produce adaptive responses and analytics.

We also created:

real-time telemetry simulation engines adaptive mission routing logic AI orchestration layers cognitive analytics pipelines dynamic gameplay adjustment systems

The UI was designed to feel cinematic, futuristic, and emotionally engaging while still maintaining accessibility for children.

Challenges we ran into

One of the biggest challenges was designing a system that balanced:

child-friendly interaction cognitive analysis immersive gamification AI explainability

We also faced challenges while:

structuring the multi-agent architecture simulating adaptive AI workflows designing responsive futuristic interfaces managing telemetry flow between agents creating believable AI-driven interactions

Another challenge was ensuring that the platform looked production-ready while still remaining lightweight enough for rapid prototyping and hackathon development.

Creating meaningful educational AI interactions without making the platform feel overly clinical was also a major design consideration.

Accomplishments that we're proud of

We are proud of:

building a highly immersive and visually polished platform designing a believable multi-agent AI architecture implementing adaptive cognitive mission systems creating a futuristic educational healthcare experience developing a dynamic AI Companion system simulating real-time telemetry-based gameplay adaptation combining healthcare, education, and AI into a single platform

We are especially proud of how the system feels emotionally supportive rather than intimidating, making cognitive screening more approachable for children.

The autonomous agent orchestration and adaptive mission routing systems were among the most technically innovative parts of the project.

What we learned

Through DyslexiCore, we learned:

how agentic AI systems can collaborate in educational applications the importance of adaptive UX for children how telemetry data can drive intelligent gameplay personalization how AI explainability improves trust in educational healthcare systems how multi-agent systems can simulate cognitive reasoning workflows

We also improved our skills in:

frontend system design AI architecture planning React and Tailwind development telemetry-driven interfaces interactive dashboard design cognitive analytics visualization

Most importantly, we learned how technology can be designed to support learning differences with empathy and accessibility.

What's next for DyslexiCore

In the future, we plan to expand DyslexiCore into a fully functional AI-assisted educational healthcare platform.

Planned features include:

real speech analysis using voice AI webcam-based eye tracking emotional state detection multilingual cognitive screening personalized reading curriculum generation teacher collaboration systems longitudinal cognitive progress tracking real PDF report generation cloud-based telemetry pipelines secure educational analytics infrastructure

We also plan to integrate real Jac autonomous workflows and deploy the platform as a scalable web application for schools, parents, therapists, and educational institutions.

Our long-term vision is to make early cognitive screening more accessible, engaging, intelligent, and emotionally supportive for children worldwide.

Built With

• css3
• html5
• jac
• react
• tailwind
• typescript
• vite