Geometry Solver and Calculator positions itself as a comprehensive educational tool for mathematics students and educators. Developed by Rudolf Halmi for iOS devices, the application has achieved recognition including #11 ranking in Mobile Learning in Action's Math category and certification from the Educational App Store, establishing credibility in the educational technology space. The application's core functionality revolves around its extensive database of over 100 geometric shapes, each with detailed property analysis capabilities. The AI-powered scanning feature represents the most advanced component, allowing users to capture word problems through device cameras for automated solving. Beyond this, the app provides systematic calculations for volume, surface area, perimeter, and circumference across both two-dimensional and three-dimensional shapes. The visualization tools enable users to rotate and examine geometric forms from multiple angles, enhancing spatial understanding. User experience centers around a clean, intuitive interface organized by shape categories and calculation types. The step-by-step solution feature breaks down complex problems into manageable stages, making it particularly valuable for learning purposes. Real-world usage patterns suggest students primarily employ the app for homework assistance, exam preparation, and conceptual reinforcement. The interface maintains consistent navigation despite the complexity of mathematical operations, though some advanced features require multiple taps to access. With no specific user reviews available for analysis, the application's 4.26/5 rating suggests generally positive reception. The absence of detailed user feedback prevents specific commentary on usability pain points or standout features from the consumer perspective. This gap in user-generated content makes independent verification of claims challenging. The application demonstrates particular strength in educational contexts where visual learning enhances comprehension. Limitations include dependency on camera quality for AI scanning accuracy and potential over-reliance for academic work. Ideal use cases involve supplemental classroom learning, homework verification, and conceptual reinforcement rather than primary instruction.