Real Estate Prices
Predict home prices based on historical sales and property details.
Business problem
Understanding fair market value is critical for realtors and investors. Accurate pricing helps clients make better buying and selling decisions.
Heimdall solution
Publish property sales and features as gold datasets in Lake, then train a regression model in Heimdall ML. Teams get price predictions without writing training code.
Business impact
Regression models help firms bid confidently — Heimdall ML delivers strong accuracy on structured property features.
How it works
Catalog property data in Lake
Ingest sales history, square footage, location, and amenities into bronze and silver.
Train ML regression
Select gold features and launch a no-code regression model with explainability.
Deploy price predictions
Use REST APIs to score new listings in your apps or workflows.
See Heimdall in action
Share your property data and pricing goals
Key benefits
Faster valuations
Score listings in seconds
Explainable features
See which attributes drive price
No-code training
Analysts build models without Python
Gold governance
One approved dataset for all models
API deployment
Production endpoints with monitoring
Retrain on refresh
Update when new sales hit Lake
Related use cases
More scenarios on the use cases hub.