Visual Data-Driven
Ecosystem for Real Estate
Client Background
Our client is a real estate company focused on improving property valuations and identifying investment opportunities by utilizing advanced data sources. Their goal was to enhance the accuracy of property listings and price predictions while uncovering hidden features that would increase the appeal of properties.
Challenge
The client needed a solution that could deliver highly accurate property valuations and price predictions based on a variety of complex data sources. These included high-resolution photographs, aerial and satellite imagery, infrared and thermal imaging, LiDAR scans for 3D modeling, and user-generated content from social media. The challenge was to process and analyze this diverse data effectively to uncover new investment opportunities and emerging market trends.
Solution
Our team developed an advanced AI-driven solution using Convolutional Neural Networks (CNNs) for object detection and segmentation. This allowed the system to analyze various data types, including images and 3D models, to provide highly accurate property valuations. The system also utilized 3D reconstruction techniques to create detailed property models, incorporating multi-modal learning to combine insights from different data sources, such as social media content and thermal imaging, for a comprehensive analysis.
Business Value
Increased engagementProperties with AI-enhanced listings saw a 50% increase in engagement, as the AI-generated insights and highlighted features attracted more attention from potential buyers.
Faster salesThe implementation of AI tools led to a 30% reduction in the time properties stayed on the market, allowing the client to close deals more quickly.
Enhanced property featuresThe AI system discovered 20% more sellable features per property on average, helping the client better market their listings and attract higher offers from buyers.
Tech Stack:
AI
CNN
Our clients journeys
