visual-preference-to-property-matching
Analyzes images of homes that appeal to users and matches them against the MLS database to find similar properties in the market. Uses visual AI to understand aesthetic preferences, architectural styles, and spatial layouts from user-provided images.
aesthetic-preference-learning
Learns user aesthetic preferences through interaction with matched properties, refining future recommendations based on which properties users engage with, save, or dismiss. Builds a personalized style profile over time.
spatial-requirement-interpretation
Extracts spatial and layout requirements from user images or descriptions, understanding factors like room count, open floor plans, ceiling height, and spatial flow to match against property specifications.
saved-search-management
Allows users to save and organize property searches, search criteria, and matched results for future reference and comparison. Provides persistent storage of user preferences and search history.
property-comparison-analysis
Enables side-by-side comparison of multiple properties with visual and data-driven analysis of differences in price, features, location, and aesthetic qualities. Helps users evaluate trade-offs between options.
real-time-listing-updates
Provides real-time access to current MLS listings and property data, ensuring users see the most up-to-date information on available properties, price changes, and new listings matching their criteria.
neighborhood-context-discovery
Provides information about neighborhoods associated with matched properties, including market trends, amenities, demographics, and local insights to help users understand the broader context of potential homes.
agent-consultation-preparation
Helps users narrow down property preferences and prepare for agent consultations by organizing matched properties, preferences, and key criteria into actionable information for professional guidance.