AI Remodel: Interior Design positions itself as a practical tool for home design enthusiasts and professionals seeking to visualize spatial arrangements through artificial intelligence. Developed by Dmytro Bubela for Android devices, the application leverages machine learning to generate room layouts, furniture placements, and decorative schemes based on user inputs and room dimensions. The core functionality revolves around an AI-powered room planner that processes room parameters and user preferences to produce multiple design options. Features include 3D visualization, style customization, and layout experimentation without requiring technical design skills. The AI engine suggests furniture arrangements, color palettes, and decorative elements while allowing users to modify proposals in real-time. This functionality addresses common pain points in interior design, such as spatial planning and aesthetic coordination. User experience centers on an intuitive interface where users upload room dimensions or select preset templates. The process involves selecting design styles (e.g., modern, minimalist, rustic), specifying room purposes, and reviewing AI-generated proposals. The 3D rendering provides realistic previews, though performance may vary based on device capabilities. Real-world usage patterns show most users employ the app for pre-renovation planning or furniture purchasing decisions, with sessions typically lasting 10-15 minutes per room. User feedback indicates generally positive reception with consistent praise for visualization capabilities. Sayed Mrizada (August 7, 2025) noted the app helped avoid physical rearrangement during moving, while Lahor Khan Syall (August 13, 2025) appreciated the time savings despite occasional layout inaccuracies. Multiple reviews from Hashmatullah Abdulrahimzai (June 25, 2025) highlight creative suggestions but note occasional room angle miscalibrations. These observations suggest reliable core functionality with minor spatial recognition limitations. The application demonstrates strongest utility for conceptual planning and inspiration generation, particularly for users lacking formal design training. Limitations include occasional spatial measurement errors and dependency on user-provided room parameters. Optimal use cases involve medium-sized residential spaces rather than complex architectural projects, with greatest value for renters and homeowners undertaking decorative updates rather than structural renovations.