Crib

Creating an Your AI-powered gateway to real estate

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Inspiration

While browsing property listings online, we noticed that static images often fail to provide clients with a comprehensive understanding of a property. To address this, we developed Cric, an immersive tool designed to enhance the property viewing experience, by creating a immersive 3D tour for the properties.

What it does

Crib is an AI-powered real estate exploration platform that combines:

  • Intelligent property search using semantic AI matching
  • Immersive 360° virtual tours with interactive hotspots
  • AI Chat Assistant for real-time, context-aware property recommendations
  • Secure dashboards for personalized property management
  • Real-time updates powered by Socket.IO

How we built it

Frontend: React + TypeScript with Vite for fast builds, TailwindCSS + ShadcnUI + Radix UI for styling and components. Implemented Socket.IO for live updates and chat.

  • Backend: Flask + Flask-SocketIO for API and real-time features. MongoDB for scalable storage of property data.
  • AI Integration: LangChain + Google Generative AI for natural conversations, FAISS vector search for semantic property recommendations.
  • Virtual Tours: Built 360° interactive tours with smooth scene transitions and room-to-room navigation.
  • Security: Added protected API endpoints, authentication, and input sanitization.

Challenges we ran into

Handling AI conversation context with LangChain required prompt engineering and memory management.

  • Implementing smooth 360° scene transitions without lag was challenging on lower-end devices.
  • Ensuring real-time synchronization of property updates and chat messages across multiple clients.
  • Designing a scalable architecture that could handle future expansion.

Accomplishments that we're proud of

  • Successfully integrated AI + real-time systems into a single cohesive platform.
  • Built an immersive virtual tour experience with interactive navigation.
  • Achieved a scalable and modular architecture with clear separation of concerns.
  • Created a secure and user-friendly dashboard for property management.

What we learned

  • How to combine Generative AI and LangChain with real-world applications.
  • The practical benefits of vector similarity search (FAISS) in semantic recommendation systems.
  • Deepened our understanding of real-time communication with Socket.IO.
  • The importance of balancing performance, security, and user experience in a complex app.

What's next for Crib

  • Integrating payment and booking systems for end-to-end property management.
  • Adding multi-language support to make the platform accessible globally.
  • Enhancing AI assistant capabilities with richer property insights and market trends.
  • Scaling the platform to support real estate agencies and marketplaces.

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