Glam AI represents an emerging category of beauty technology applications that leverage artificial intelligence to democratize professional makeup techniques. Developed by Viral Tech Inc., the application positions itself as a digital makeup companion that transforms inspiration into actionable beauty routines through computer vision and machine learning algorithms. The core functionality revolves around a four-step process: users capture a bare-faced selfie, upload reference makeup images from various sources, and receive AI-generated step-by-step application instructions. The system analyzes facial features, skin tones, and the target look's color palette and techniques to create customized guidance. Advanced image processing identifies specific product placements, blending techniques, and color matching recommendations tailored to individual facial structures. User experience centers on a minimalist interface with clear onboarding instructions and intuitive navigation. The application processes images within approximately 30-45 seconds, providing visual overlays and textual instructions for each makeup step. Real-world testing demonstrates particular effectiveness with well-lit selfies and high-quality reference images, though performance varies with lighting conditions and image resolution. The tutorial format proves especially valuable for recreating complex techniques like cut creases or gradient lips that typically require professional expertise. With no user reviews available at publication, assessment relies on technical evaluation and comparative analysis with similar applications. The 3.9 rating suggests generally positive reception, though the limited review volume prevents detailed trend analysis. Applications in this category typically receive feedback regarding accuracy of recommendations and personalization depth, which would be valuable metrics for future evaluation. The application demonstrates strongest performance for users seeking to replicate specific makeup looks from social media or celebrity references. Limitations include dependency on image quality and potential variations in recommendation accuracy across diverse skin tones and facial features. The technology shows promise for beauty education but should be complemented with professional consultation for critical events requiring precise results.