Romonet Partners With Stanford University
Romonet provided data center predictive modeling tools and services for the prestigious west coast research and teaching institution’s new research facility.
Romonet has announced that it has worked with Stanford University, one of the world’s leading research and teaching institutions, to model its new $41 million research computing facility.
StanfordUniversitywill also employ Romonet’s innovative software products through the full life-cycle of its new and existing data center facilities with a strong emphasis on predicting and controlling operational and financial performance of the facility.
“Our clients and the wider industry are at an inflection point where demonstrating the financial impact of engineering and operational business decisions is imperative,” said Zahl Limbuwala, CEO of Romonet. “We are very pleased to be working with such a prestigious organization. Stanford University will benefit greatly from understanding the financial and efficiency implications of the decisions it makes through the life cycle of its new facility.”
Romonet introduced its award winning Romonet Software Suite in November 2010, with the aim of helping businesses run their data centers in a more efficient and cost effective manner. The unique predictive modeling capabilities allow clients such as Stanford University to control costs and reduce risk, by improving financial forecasting of data center equipment, IT platforms & workloads.
Romonet Software Suite is a suite of applications for financial, operational and engineering teams, bringing together the world of data center engineering and operations with finance. Because Romonet models the environment rather than metering it, the software can provide decision-making data before decisions are made, enabling organizations to make more informed decisions. Most importantly, Romonet Software Suite enables organizations to track and verify key operational and financial indicators on a regular basis thereby delivering previously unavailable cost- and efficiency-optimized performance.