The Challenge of Spatial AI
Most Generative AI models are great at making "pretty pictures," but they often fail at spatial logic. For interior design, a simple image generation isn't enough. If an AI places a sofa that’s 10 feet long in a 5-foot space, the tool is useless for real-world space planning.
As an R&D engineer with a background in system architecture, I wanted to see if we could bridge the gap between AI tools and functional 3D visualization. This led to the development of JanvAI.
Our Technical Approach
To build a reliable room render engine, we had to move beyond basic API calls. Here’s a breakdown of the stack we used:
Intelligence Layer: We integrated Google Gemini (Pro/Flash) to handle complex Natural Language Queries (NLQ). By fine-tuning our prompts, the AI acts as an interior design assistant that understands specific architectural styles—from Parisian gypsum roses to modern earthy textures.
The "Context" Problem: One of the biggest hurdles was maintaining the room's structural integrity. We’ve been experimenting with the Model Context Protocol (MCP) to allow our AI agents to better understand user-uploaded data and local environment constraints.
Performance & Scale: The backend is powered by PHP (Laravel) for robust API management, paired with Python scripts for heavy data processing and optimization.
DevOps Excellence: To ensure seamless updates, we use Docker and Ansible to manage our multi-server deployment pipeline. This allows us to push new 3D visualization features without downtime.
Key Features of JanvAI
We didn't just want another "filter" app. We built JanvAI to be a comprehensive design companion:
High-Fidelity Rendering: Transform a messy room photo into a professional interior concept in seconds.
Style Consistency: Whether you're looking for home decor inspiration or a full renovation plan, the AI maintains a consistent aesthetic across different angles.
Visualizing the Impossible: For those awkward spaces—like a 3.5ft deep mantel—our tool helps users visualize layers and scale before they spend a dime.
What's Next?
The next frontier for us is deeper integration with 3D visualization libraries to allow users to interact with individual decor objects in real-time.
Building a side project as an engineer is always a journey of constant learning—from troubleshooting Cloudflare tunnels to optimizing SQL queries for large-scale data syncs.
Try it out and let me know your thoughts: https://www.janvai.com/
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