“What DataRobot allows them to do is a lot of the same things automatically, and they can focus their time on where their managerial talent is more valuable, like generating new features or understanding the data better.”

"As a commodity, steel can range from $500 to $1,000 per ton. By reducing our scrap rates and being more consistent job to job, we can generate significant annual savings for the business."

“We didn’t have the tools to do this at scale. Analytics were accurate, but they were slow. If we could accelerate that model building process, that would be a huge advantage to us.”

"I thought there was a faster way to do model development and validation, and DataRobot gave us the flexibility to build certain models that we weren’t currently building and ensure those models met the high bar for regulatory compliance."

"DataRobot allows our IT developers to pick up supervised machine learning easily. It lowers the steep curve of machine learning and removes the complexity of the underlying models from the developers."

“We always keep ourselves up-to-date on the latest data science trends and options available, through talking to partners and performing technology scanning."

"When we start to seriously think about investing in a predictive analytics platform, ROI emerges as a key consideration. Ideally it would be an enterprise-level software – like DataRobot – that we can extend usage and scale for other purposes."

"We use DataRobot to make billions of predictions."

"DataRobot turns my three data scientists into a team of 20 data scientists."

"DataRobot gives you all the tools you need. It will democratize machine learning across the whole business."

"I had a team of analysts doing predictive analytics, but we were shoehorned into using generalized linear models (GLMs) and doing that manually. These projects would typically be very, very long — three to six months — and as soon as they’re finished, they’re pretty much out of date."

“My high-level vision of the architecture is that Snowflake is the hub.”

“What DataRobot allowed us to do was take our historical data in Snowflake and easily train, test, optimize, and deploy business learning models into our production environment to easily create business value.”

“I find DataRobot to be a great tool for accelerating the application of data science, and we should think about harnessing data science to improve our work. That leaves the organization to focus your resources on where you add value.”

"It was difficult to go from raw data to prediction insights that could be integrated into the business. It wasn’t until we became a centralized team, developed a comprehensive analytics strategy and sourced a standardized tool like DataRobot that we, as a data science function, began to deliver real value …