Contact Us

Automatic valuation model to use predictive models in the real estate industry

Auto Valuation Model

Challenge

Keller Williams wanted to strategically pivot into iBuying where they use predictive models to buy and sell real estate online.

Solution

KUNGFU.AI developed a proprietary XGBoost, Tree-based ML model that can predict home values accounting for thousands of structured and unstructured features. We  established a human-in the loop training systems where brokers can give feedback and train the models.

Auto Valuation Model

Outcome

Solution helped Keller Williams generate a new revenue stream which is currently being piloted in three markets.

Gradient Boosted Trees

Auto Valuation Model

Challenge

Keller Williams wanted to strategically pivot into iBuying where they use predictive models to buy and sell real estate online.

Solution

KUNGFU.AI developed a proprietary XGBoost, Tree-based ML model that can predict home values accounting for thousands of structured and unstructured features. We  established a human-in the loop training systems where brokers can give feedback and train the models.

Auto Valuation Model

Outcome

Solution helped Keller Williams generate a new revenue stream which is currently being piloted in three markets.

Gradient Boosted Trees

Download the Case Study

More case studies
The Waste Management Early Alert Rear Safety Device
Object Detection

Waste Management Early Alert Rear Safety Device

Realty Austin Case Study cover
Recommendation Modeling

Case Study: Realty Austin

Realty Austin needed to improve the available housing recommendations sent to its customers via email. Find out how KUNGFU.AI created the system that generated significantly improved email click-through rates.
Case Study: Natural Language Processing for Audio Search, a broadcaster records a podcast that will then be indexed and archived with NLP
Natural Language Processing (NLP)

NLP for Audio Search