Case Study: Dejalytics achieves faster energy price forecasting with Xpanse AI

Energy Price Forecasting Simplified With Xpanse Technologies

Dejalytics, an analytics firm for energy companies based in Texas, faced the significant challenge of predicting violent and costly price spikes in the wholesale energy market. Their CEO, David Inbar, explained that while they collected vast amounts of data, the process of manually reshaping it for analysis was a massive undertaking, requiring resources they didn't have. They needed a way to quickly test thousands of hypotheses to find predictive signals without an army of data engineers.

Xpanse AI implemented its automated data science technology to address this challenge. Their solution automated the heavy lifting of data wrangling and feature engineering, building predictive models directly from Dejalytics' raw databases. This enabled the Dejalytics team to experiment with different forecasting targets at unprecedented speed. The measurable result was a dramatic reduction in model delivery time, down from months to just days or even hours, providing critical time savings for their business.

Dejalytics

David Inbar

Chief Executive Officer