Design Sense is a mobile app that uses AI to generate interior and exterior design renders from user-uploaded photos. It processes images to apply over 32 predefined styles, including modern, minimalist, and Zen, across 34 room categories like kitchens, offices, and gardens. The core functionality involves uploading a photo, selecting a style and optional color palette, and receiving multiple rendered outputs in seconds via generative AI models optimized for spatial consistency. Recent updates include an Inpaint function for targeted edits and bug fixes for smoother performance.
The tool supports both iOS and Android platforms, with a free version offering limited renders and a premium tier for unlimited access and watermark-free exports. Compared to competitors, it provides broader exterior design options than RoomGPT, which prioritizes indoor color experiments, and faster generation times than Interior AI, focused on real estate staging. Pricing follows a freemium model, generally lower entry cost than specialized tools like REImagine Home, which emphasize virtual reality previews.
Key features include style application that maintains room proportions, prompt-based customizations for elements like furniture, and export options for sharing designs. Users report high satisfaction with visualization speed for DIY projects, though some note occasional inaccuracies in object scaling on complex photos. A surprise capability is rendering from sketches, extending use beyond photos to conceptual ideas.
The AI employs computer vision to detect room elements and diffusion models to blend styles, ensuring outputs align with real-world feasibility. It integrates no external software but allows direct app downloads from stores. Positive aspects include accessibility for non-professionals and quick iterations; drawbacks encompass limited manual adjustments and dependency on photo quality.
Test the app with high-resolution images in good lighting, iterate on styles for best results, and combine outputs with physical measurements for accurate implementations.