Think of this as a very fast, very patient analyst that reviews mountains of real-estate and financial data for you, then flags which properties look like good buys, which you should keep, and which you might want to sell.
Individual and professional real-estate investors struggle to process all the data needed to decide when to buy, hold, or sell properties (market trends, comps, rental demand, interest rates), leading to slow, biased, or suboptimal decisions.
Access to proprietary transaction data, local market performance histories, and investor behavior patterns, combined with models tuned for real-estate investment workflows (deal screening, underwriting, portfolio review).
Hybrid
Vector Search
Medium (Integration logic)
Data quality and coverage across markets (MLS feeds, transaction histories, rental data) will constrain model accuracy and generalizability more than raw compute.
Early Majority
Positioned specifically around the investor decision cycle (buy/hold/sell) rather than generic home search or valuation, likely emphasizing portfolio-level analytics, scenario testing, and risk/return optimization for real-estate investors.