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Development of Cross-Platform Financial Insights Mobile App MVP with Enhanced User Engagement Features
  1. case
  2. Development of Cross-Platform Financial Insights Mobile App MVP with Enhanced User Engagement Features

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Development of Cross-Platform Financial Insights Mobile App MVP with Enhanced User Engagement Features

netguru.com
Financial services
Information technology

Key Challenges Identified

Lack of detailed specifications for interface development, need for complete UI/UX overhaul, high user entry barriers due to complex financial concepts, absence of knowledge-sharing features, tight 5-week deadline for conference alignment, and requirement to appeal to both early adopters and mainstream investors while maintaining technical excellence.

About the Client

Transformative fintech startup leveraging AI to democratize access to financial markets through real-time stock data analysis and predictive insights

Strategic Project Goals

  • Develop cross-platform iOS/Android MVP within 5 weeks
  • Redesign UI/UX for mainstream investor accessibility
  • Implement knowledge-sharing features to reduce entry barriers
  • Ensure timely deployment for November conference acquisition
  • Maintain high code quality and performance standards
  • Address security and accessibility requirements proactively

Core System Requirements

  • Real-time AI/ML stock market analysis dashboard
  • Portfolio tracking with global company grouping
  • Interactive educational content modules
  • Community-driven signal interpretation forums
  • Personalized investment opportunity alerts

Technology Stack

React Native
JavaScript
Redux
Firebase

System Integrations

  • Real-time financial data APIs
  • Third-party authentication services
  • Cloud-based ML model deployment

Quality Attributes

  • Sub-2-second screen load times
  • FINRA-compliant data security
  • Horizontal scalability for 100k+ users
  • WCAG 2.1 accessibility compliance

Expected Business Outcomes

Accelerated market entry enabling conference-driven user acquisition, 10,000+ AI models operationalizing predictive capabilities, 10 NPS score validating product-market fit, and establishment of scalable technical foundation supporting future investment rounds while maintaining budget efficiency through cross-platform development.

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