This is like an always-on digital appraiser that looks at thousands of past property sales, current listings, and local market signals to estimate what a home or building is worth—instantly and consistently—rather than waiting days for a human-written appraisal report.
Traditional property valuation is slow, manual, and subjective, leading to delays in transactions, inconsistent pricing, and higher risk for lenders, investors, and brokers. An AI-driven valuation system automates much of this analysis, delivering faster, more consistent, and data-rich price estimates at scale.
Proprietary historical transaction data, enriched with local market signals and client-specific risk rules, integrated directly into lender and brokerage workflows creates switching costs and performance advantages that are hard for generic valuation tools to match.
Hybrid
Structured SQL
High (Custom Models/Infra)
Access to clean, high-granularity transaction and listing data across geographies; model drift as markets change; and regulatory/compliance requirements around explainability for lending and appraisal decisions.
Early Majority
Positioned as a next-generation AI valuation approach that goes beyond legacy AVMs by combining machine-learning price prediction with richer feature sets (property attributes, spatial data, market trends) and potentially LLM-based explanation/report generation to make outputs more transparent and usable in real-estate workflows.