About the Project
Inspiration
Finding the right property is often a frustrating experience. Traditional real estate platforms rely on filters and endless scrolling, making it difficult for users to quickly discover properties that truly match their needs. We wanted to create a more natural and intelligent way to search for real estate by letting users simply describe what they are looking for in everyday language.
This idea inspired us to build Rust AI, an AI powered real estate platform that combines a modern property marketplace with a conversational assistant capable of understanding user preferences and recommending relevant properties.
What We Built
Rust AI is a full stack real estate platform designed to simplify property discovery. Users can browse listings, explore detailed property information, and interact with an AI assistant that provides personalized recommendations through natural language conversations.
Key features include:
- AI powered conversational property search
- Intelligent property recommendations
- Responsive and modern user interface
- Property listings with detailed information
- Authentication and user account management
- Featured and latest property sections
- AI assistant integrated using n8n workflows and OpenAI
How We Built It
We built the frontend using Next.js, React, and Tailwind CSS, creating reusable components and a responsive user experience across desktop and mobile devices.
Global state management was handled with Redux Toolkit, while API communication was implemented with Axios.
The AI assistant, Rust AI, was developed using n8n, where we designed webhook based workflows to process user messages, maintain chat sessions, and generate intelligent responses using OpenAI. The frontend communicates with the AI assistant through production webhooks, enabling users to search for properties using natural language instead of traditional filters.
For the hackathon demo, we temporarily switched the frontend to high quality dummy property data so the complete experience remains functional even without a live backend.
Challenges We Faced
One of the biggest challenges was integrating the AI assistant with the frontend while maintaining smooth conversations and reliable session management.
Another challenge was working with backend API availability during development. To ensure the project remained fully demonstrable, we adapted the frontend to use realistic dummy data while preserving the overall architecture, making it easy to reconnect to the backend later.
We also focused on designing an interface that balances functionality with simplicity, making the platform easy to use for both buyers and renters.
What We Learned
Throughout this project we gained hands on experience with:
- Building scalable applications using Next.js and React
- Creating AI workflows with n8n
- Integrating OpenAI powered conversational experiences
- Managing application state with Redux Toolkit
- Designing responsive and reusable UI components
- Handling API integration and fallback strategies
- Deploying production ready web applications
What's Next
We plan to reconnect the live backend, enhance the recommendation engine with smarter personalization, add voice based conversations, integrate interactive maps, and support multilingual interactions. Our goal is to make Rust AI a truly intelligent real estate assistant that helps users find their ideal property faster and with greater confidence.
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