Keller Williams unlocks agent efficiency with AI
Models to Production 3X Sooner
When looking for an AI partner, Keller Williams turned to the DataRobot AI Platform to automate the machine learning process and for its integration with the Google Cloud Platform.
DataRobot and Google Cloud Platform fit seamlessly into the Keller Williams AI ecosystem. We have predictive models in production and are looking to build generative models that add value and benefit our business.
For the data analytics team, DataRobot brings a low-code interface that means fast development and testing without sacrificing quality. Behind that, De Letter and the team value DataRobot’s feature engineering capabilities, easy MLOps, and rapid deployment into production.
Every month, the company derives more than four million inferences, or learnings, and finds answers to support decisions much sooner.
“Before DataRobot, it used to take a data scientist at least 3 to 6 months to prepare the data, iteratively engineer features, and train a model that we could take to market,” De Letter said. “DataRobot allows us to cut that time down to less than a month for a first iteration. We can review output much quicker with the business and they, in turn, feel much closer to the process.”
