Indiana-Trained AI That Knows Your Market

Automated valuation models trained exclusively on Indiana sales data. AVM estimates with confidence intervals, SHAP explainability, and assessment anomaly detection.

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The Problem

National AVMs underperform in Indiana because they lack local training data
Assessment-to-market divergence creates opportunities and risks that are hard to spot
Appraisals are expensive and slow for portfolio-level analysis
CMA tools don't account for Indiana-specific assessment methodology

How AI Valuation Helps

Indiana-Specific AVMs

XGBoost models trained exclusively on Indiana sales data, segmented by property class and region. Goal: beat Zillow's 7% median error rate.

Confidence Intervals

Every estimate includes a confidence range. Know when the model is certain and when it's uncertain.

SHAP Explainability

Understand what drives each valuation. Feature importance charts show which property characteristics matter most.

Assessment Anomaly Detection

Flag properties where assessed value diverges significantly from model-predicted market value. Feeds directly into tax appeal workflows.

Batch Valuation

Upload a portfolio of properties and receive valuations for all of them. CSV upload, API batch endpoint, or scheduled recurring jobs.

Frequently Asked Questions

Our target is a median absolute percentage error (MdAPE) below 7% statewide, with better accuracy in data-rich urban counties. We publish accuracy metrics by county and property class.

Parcel characteristics (size, age, condition, construction type), comparable sales, assessment history, location features (school district, flood zone, neighborhood), and macro market indicators.

Ready to Try a Valuation?

Indiana-specific automated valuation models trained on local sales data. AVM estimates with confidence intervals and SHAP explainability.

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