PrediqtHome AI

Property Intelligence Platform — Built by Dave Richert, Licensed Real Estate Agent | 22 Years Market Experience | Aurora/Naperville, Illinois

PrediqtHome AI delivers what insurance carriers, mortgage lenders, and real estate platforms have never had: continuous, verified, property-level intelligence. Our validated methodology generates two critical scores from a single home evaluation — the UHS-MV (market value) and UHS-IR (insurance risk) — giving you a real-time window into every property you underwrite, lend against, or represent.

The Problem We Solve

Insurance companies, lenders, and real estate professionals currently have no reliable way to see inside homes and track ongoing property condition. A home assessed five years ago may have had a complete HVAC replacement, a new roof, and updated electrical — or it may have deferred all maintenance. There is no way to distinguish between these scenarios today.

PrediqtHome closes three critical gaps: the visibility gap (no ongoing property condition data), the communication gap (no data to explain premium changes to customers), and the preventable claims gap (industry estimates suggest $30–40 billion annually in claims that stem from deferred maintenance).

Validated Accuracy

Our property valuation methodology has been validated across 20 blind studies — we analyze every property before knowing the actual sale price, then compare our prediction to the real outcome. No backtesting, no curve-fitting.

Overall study average error: 7.8% across all 20 properties. Most recent four properties (v10.0 methodology): 3.415% average error, with three of four rated EXCELLENT (under 5% variance).

How the System Works

Layer 1 — Universal Home Score (UHS): A comprehensive property condition assessment generating two scores. The UHS-MV (0–110 scale) captures market value positioning. The UHS-IR (0–100 scale) isolates insurance risk factors — structural systems, safety compliance, and claims-likelihood indicators — and translates directly into underwriting risk multipliers.

Layer 2 — Home Maintenance Score (HMS): While UHS captures a point-in-time snapshot, the HMS tracks ongoing homeowner behavior over time. Our 108-task maintenance program covers all twelve months of property upkeep. Homeowners who complete and document tasks earn HMS points that translate to insurance premium discounts of 10–30%. Our analysis indicates that regular HMS completion prevents 85–95% of common insurance claims and extends major system life by 20–40%.

Layer 3 — Dave Richert Comparative Pricing Framework: The valuation engine underlying both scores is built from 22 years of active real estate practice. This is not a traditional AVM. It is a systematic, room-by-room, feature-by-feature adjustment framework that accounts for construction decade cohorts, market timing psychology, buyer behavior patterns, and property-specific condition factors that automated models cannot capture.

Think of It as Telematics for Homes

Just as Progressive’s Snapshot transformed usage-based auto insurance — changing both risk assessment and the relationship between driver and insurer — PrediqtHome delivers usage-based property intelligence for homeowners insurance. Homeowners who maintain their properties finally see that behavior reflected in their pricing. Carriers gain the data to explain rate changes, reward good behavior, and prevent claims before they happen.

About PrediqtHome AI

PrediqtHome AI is designed for B2B licensing to insurance carriers, mortgage lenders, and real estate platforms. The system supports API integration with existing carrier systems, scalable property assessment workflows, and the data governance standards required for enterprise deployment. Patent documentation is prepared for the proprietary scoring and assessment systems.

Dave Richert | PrediqtHome AI

Licensed Real Estate Agent | Aurora/Naperville, Illinois

22 Years Market Experience | Patent Pending