AI Interiorflow
A project by NerdHeadz.
An AI-powered interior design platform that generates room layouts and design suggestions from photos, helping users reimagine their living spaces with intelligent automation.
What we set out to solve
AI Interiorflow set out to transform how people approach interior design by using AI to turn simple photos into fully rendered room concepts. Existing tools lacked the intelligence and ease of use needed to make professional-quality design accessible to everyone.
Core challenges included
- Processing user-uploaded room photos with accurate spatial recognition.
- Generating realistic interior design suggestions that matched user preferences.
- Building an intuitive interface accessible to non-designers.
- Scaling the AI pipeline to handle concurrent render requests efficiently.
- Integrating multiple AI models while keeping response times reasonable.
The goal was more than a simple rendering tool — it was about creating an intelligent design assistant that could understand context, style preferences, and spatial constraints to produce meaningful results.
Building the Right Solution
Key objectives included
Build an AI engine that accurately interprets room layouts and generates contextually appropriate design suggestions.
Create a seamless user experience from photo upload to rendered design output with minimal steps.
Together, these objectives shaped a platform that makes professional interior design accessible through the power of AI, turning any room photo into a source of design inspiration.
How we built it
AI Interiorflow was developed through a structured process that combined AI research with user-centered design principles.
Each phase focused on delivering reliable, high-quality design generation while maintaining a smooth user experience.
Development process
Planning
Defined the AI pipeline architecture and outlined user workflows for photo upload, style selection, and render output.
Design
Created the showcase, render management, and generation interfaces with clear navigation and visual feedback.
Development
Built the platform with a Python-powered AI backend and a Bubble frontend, integrating image processing and render generation modules.
Testing
Validated AI output quality, render accuracy, and user flow smoothness through detailed QA across multiple room types.
Launch
Released the platform with core features including photo upload, AI-driven redesign, and a personal render gallery.
What it delivered
- AI engine accurately interprets room layouts and generates contextually appropriate design suggestions from uploaded photos
- Users receive multiple professionally styled redesign options in seconds from a single room photo
- Python-powered AI backend handles concurrent render requests with consistent output quality
- Bubble frontend delivers a seamless experience from photo upload to rendered design with minimal steps
- Personal render gallery allows users to save, compare, and revisit AI-generated room designs
What we owned
Project Manager
Anahit Hakobyan
AI, Backend & Frontend Development
Alesya Marova
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