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Development of AI-Enhanced Medical Education Platform with Cross-Platform Applications

10clouds.com

Education

Medical

Current Challenges in Platform Scalability and Technology Integration

Quesmed faces challenges in scaling its platform due to outdated technology stacks, inconsistent development practices from previous outsourcing partners, and the need for advanced features to maintain competitive edge in the EdTech market.

About the Client

A UK-based medical education technology startup operating in 20+ countries, providing interactive learning resources for medical students and professionals

Strategic Development Goals

Implement generative AI capabilities for personalized learning experiences
Enhance platform scalability to support 50,000+ concurrent users
Develop interactive assessment modules with real-time feedback
Create a unified design system across all digital touchpoints
Integrate machine learning for competency tracking and performance analytics

Core System Requirements

Cross-platform mobile applications (iOS/Android) with React Native
AI-powered content recommendation engine
Interactive clinical scenario simulations
Real-time competency assessment dashboards
Multi-language support for global users
Secure user authentication with role-based access control

Technology Stack Requirements

Node.js

React.js

React Native

Python

TensorFlow

AWS Cloud Services

System Integration Needs

Medical licensing databases
Payment gateway for subscription management
Third-party content APIs
Learning Management System (LMS) standards compliance

Performance and Security Requirements

99.9% platform uptime with auto-scaling capabilities
HIPAA-compliant data security measures
Sub-200ms response time for critical API endpoints
Automated CI/CD pipeline with test coverage >85%
Accessibility compliance (WCAG 2.1 AA)

Anticipated Business Outcomes

Projected 300% increase in user engagement metrics, expansion to 30+ countries within 18 months, and 40% reduction in customer support inquiries through improved UX. The AI implementation is expected to drive a 20% improvement in user certification rates.