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Development of Scalable Career Guidance Platform with AI Integration
  1. case
  2. Development of Scalable Career Guidance Platform with AI Integration

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Development of Scalable Career Guidance Platform with AI Integration

knubisoft.com
Education
Information technology
Media

Challenges in Career Guidance for Adolescents

Lack of accessible, personalized career guidance for teenagers (13-14 years old) combined with technical challenges including absence of ready-made backend infrastructure, tight budget/deadline constraints for MVP development, and significant mid-project design changes requiring rapid adaptation while maintaining scalability for future expansion to 1,000+ UK occupations.

About the Client

UK-based EdTech company supported by IBM, combining AI, broadcast media, and career guidance to transform educational and career discovery for students and adults

Objectives for MVP Development

  • Create scalable minimum viable product for career discovery platform
  • Develop dual user flows for profile creation and profession video exploration
  • Implement AI-powered chatbot with IBM Watson integration
  • Adapt to dynamic design changes during development
  • Demonstrate investor-ready prototype with expansion capabilities

Core Platform Capabilities

  • User profile creation with interest/motivation tracking
  • Video-based profession exploration interface
  • IBM Watson chatbot for career guidance queries
  • Modular backend architecture for future occupation expansion
  • Cross-platform responsive design

Technology Stack Requirements

React
TypeScript
IBM Watson
IBM Watson Discovery
Figma

System Integration Needs

  • IBM Watson AI chatbot
  • UK National Careers Database API
  • Multi-platform support (iOS/Android/SmartTV)

Operational Requirements

  • Horizontal scalability for 1,000+ professions
  • 99.9% uptime SLA
  • WCAG 2.1 accessibility compliance
  • Sub-2s page load times
  • Role-based access control

Expected Business Impact

Enables personalized career path decision-making for adolescents through AI-driven insights while providing investors with demonstrable scalability. The platform's modular architecture will reduce future development costs by 40% when expanding to new professions, with IBM Watson integration ensuring continuous improvement in career recommendation accuracy through machine learning.

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