Sustainable Architect AI

Inspiration

AI has transformed fields like medicine, finance, and art — but in architecture, its potential is still largely untapped. Sustainable design often relies on manual analysis or post-project audits, which are slow and limited in scope. We saw an opportunity to bridge that gap. Sustainable Architect AI was born from the idea that AI shouldn’t just generate pretty visuals — it should actively help architects make smarter, greener design decisions. Our goal was to create a tool that leverages AI to evaluate sustainability early in the design process, offering real, actionable insights rather than generic recommendations.

What it does

Sustainable Architect AI uses AI to analyze building designs or images and provide actionable sustainability insights. Users can describe a building concept in text, and EcoArchitect generates a detailed report — highlighting pros, cons, and suggestions across lighting, materials, energy efficiency, and environmental integration. It also gives each design a sustainability score, making it easy to benchmark and improve over time.

How we built it

We built Sustainable Architect AI using React and TypeScript for a responsive, modular frontend and integrated the Gemini API for AI-driven sustainability analysis of descriptions. MongoDB handles user authentication and stores building analysis history. This full-stack setup lets users log in, look up designs and instantly receive actionable sustainability insights powered by AI.

Challenges we ran into

We faced several challenges throughout development — from resolving GitHub merge conflicts during collaboration to refining feature implementations across the frontend and backend. The biggest hurdle was prompt engineering: structuring requests to the Gemini API in a way that consistently produced accurate, insightful sustainability analyses instead of generic responses.

Accomplishments that we're proud of

We’re proud of creating a reliable, full-stack platform that applies AI meaningfully in sustainable architecture. A major accomplishment was developing a custom grounding gem for the Gemini API, designed to anchor the model’s responses in accurate, domain-specific sustainability data. This greatly reduced hallucinations and improved the consistency of analyses, ensuring that feedback on materials, energy efficiency, and design recommendations stayed realistic and technically sound. We’re also proud of how seamlessly we integrated this with a clean, React-based UI for an intuitive user experience.

What we learned

We learned how powerful multimodal AI can be when combined with design tools — and how much prompt structure matters in getting useful, repeatable responses. We also deepened our understanding of sustainable design principles, realizing how much early feedback can change architectural outcomes.

What's next for Sustainable Architect AI

We plan to complete features that didn’t make it into our final build, including direct user image uploading that allows users to take photos of real buildings and receive instant, AI-driven sustainability feedback. This will make Sustainable Architect AI more interactive and practical, enabling on-site evaluations and real-time suggestions for improving energy efficiency, material use, and overall sustainability.