Cherre

Cherre is a sophisticated Machine Learning-driven data integration and insights platform specifically engineered for the commercial and residential real estate sectors. By 2026, it has solidified its position as the central nervous system for institutional real estate investors, utilizing a proprietary Knowledge Graph to resolve disparate datasets into a single source of truth. The platform's core technical architecture leverages advanced Entity Resolution (ER) to connect internal portfolio data with thousands of external public and private data sources (tax, deeds, demographics, and foot traffic). Its 2026 market position is defined by its transition from a simple data warehouse to an 'Autonomous Underwriting' engine, allowing firms to programmatically evaluate opportunities against real-time market shifts. Cherre provides the underlying infrastructure that enables data scientists to bypass the 'data cleaning' phase, which traditionally consumes 80% of ML projects, offering 'ML-ready' datasets via Snowflake, Databricks, or a robust GraphQL API. This allows for hyper-accurate predictive modeling on asset valuations, cap rate compression, and risk assessment at a granular parcel level.