Espai
An AI-powered interior design assistant utilizing diffusion models for real estate staging and space redesign.
Want to see how we did it?
Read our dedicated technical deep dive into the architecture, challenges, and prompt engineering behind Espai Regen.
Overview
Espai (pronounced ess-pie) is a tool built to simplify interior design and furniture discovery using computer vision and generative AI. It began as a personal utility to visualize how furniture from Pinterest or styled room images would look in a personal space, later evolving into a fully featured product bridging the gap between aesthetic inspiration and practical implementation.
The Challenge
The primary goal was to automate the tedious process of identifying furniture in images and finding purchase options. It required solving complex problems like advanced image segmentation, object detection, and image-to-image AI workflows to professionally restyle or stage rooms digitally.
Key Features
- ★AI-powered furniture identification
- ★Computer vision for object detection & segmentation
- ★Generative AI for room restyling
- ★Reverse search for purchase links
- ★Digital room staging & placement
The Solution & Workflow
1. Identification
Integrated Google's OWL-ViT with OpenCV to allow users to select individual furniture items and get real-time shopping links.
2. Restyling
Implemented Stable Diffusion XL to transform entire rooms into different interior aesthetics (e.g., mid-century to minimalist).
3. Staging
Used edge detection and inpainting workflows to mask objects and regenerate background content cleanly.
Gallery
Outcomes
Espai validated core ideas around practical visual AI and resonated with early testers. While it was eventually sunsetted to focus on newer ventures, it served as a robust technical foundation for generative product work.