According to a new press release, “Earnix, Ltd., a leading provider of advanced analytics solutions for the financial services industry, and DataRobot, the pioneer in automated machine learning, announced a strategic alliance that delivers a new level of AI-driven insights in high-performance, real-time production systems. Through the use of best-in-class machine learning, users of the integrated solutions will dramatically increase the speed and accuracy of their analytic applications, enabling greater market responsiveness and improved business results. The two companies announced the availability of a seamless integration between the solutions allowing models created in DataRobot’s automated machine learning platform to be easily integrated into the Earnix’s market leading pricing and risk modeling platform in a fraction of the time of traditional methods. Users of the Earnix solution will be able to combine DataRobot’s machine learning models with traditional regression analytical models. Marquee financial services customers are already using the integrated solutions in their applications and realizing greater precision and time-to-market.”
The release goes on, “According to Seann Gardiner, SVP of Business Development at DataRobot: ‘Accelerating AI success through best-in-class automated machine learning is what we are focused on. We’re excited to be working with Earnix, an innovator in analytics, to offer the financial services industry a best-of-breed solution that will give our joint customers a competitive advantage in the marketplace.’ According to Udi Ziv, Earnix CEO: ‘We are providing our clients with the tools, techniques, and technology needed to produce significant business results from advanced analytics. We are delighted to be working with DataRobot to empower users of all skill levels to develop and deploy highly accurate machine learning models within Earnix applications at scale. The joint solution delivers on our vision of Customer Centric Digital Transformation’.”
Read more at Business Wire.
Photo credit: Earnix