AI-Driven Design Recommendations
Advanced machine learning algorithms and spatial analysis to offer personalized design suggestions.
Service Description
Generate floor plans, layouts, and furniture arrangements based on user preferences, space dimensions, and functionality requirements. Provide real-time suggestions for improving space utilization and aesthetics. 1. Space Analysis Input: Users upload room dimensions, layouts, or photos. Processing: Analyze spatial parameters like size, proportions, and obstructions (e.g., windows, doors, beams). Detect existing furniture or fixtures using image recognition. 2. Design Style Suggestions User Input: Style preferences (e.g., modern, minimalist, traditional, bohemian). Functional requirements (e.g., workspace, kid-friendly, eco-friendly). AI Output: Generate customized design styles with furniture arrangements, color palettes, and decor themes. Include mood boards for inspiration. 3. Smart Layout Optimization Functionality: Optimize furniture placement for aesthetics and flow (e.g., balance between open space and seating areas). Suggest storage solutions for clutter-free living. Provide multiple layout options to suit various preferences. 4. Color and Material Matching Input: Users select base colors, materials, or themes. AI Output: Suggest complementary colors and textures. Provide curated options for wall paint, flooring, furniture finishes, and decor materials. 5. Budget-Conscious Design Options Feature: Recommend furniture and materials within a specified budget range. Balance cost-effectiveness with aesthetic appeal. 6. Sustainability Recommendations Suggest eco-friendly materials, energy-efficient lighting, and sustainable furniture. Highlight the environmental impact of each design choice. 7. Adaptive Learning The AI adapts to user preferences over time, improving the relevance of recommendations based on previous projects and feedback.