New York-headquartered Opera Solutions, LLC, founded by the entrepreneur of Indian origin Arnab Gupta, has raised $84 million by selling an undisclosed minority stake to a group of investors led by Silver Lake Sumeru, with further participation from Accel?KKR, Invus Financial Advisors, JGE Capital Management and Tola Capital.
This is the first round of outside equity funding for Opera. The equity financing, said to be one of the largest ever for a private firm in the Big Data predictive analytics space, will be used as growth capital, according to the company.
Arnab Gupta, founder and CEO of Opera Solutions, said, “Opera’s core value lies in turning Big Data into Small Data – that is, using advanced machine intelligence to extract valuable signals and patterns from massive data flows and turn them into a stream of analytically enriched guidance, brought to the front lines of our customers’ businesses.”
Prior to Opera, Gupta had founded and sold a number of other companies, including Mitchell Madison Group and Zeborg, a business intelligence software firm. He began his career with McKinsey & Co., where he was a Partner, and also served as a Partner at A.T. Kearney.
Opera creates and provides hosted delivery of a suite of analytics solutions to market-leading companies in financial services, government, healthcare and other sectors. Its solutions are powered by its Big Data analytics and signals processing platform. Founded in 2004, the company has 600 employees and offices in North America, Europe and Asia.
Ben Bisconti, managing director of Accel-KKR, said, “With 160 scientists, Opera has built one of the leading advanced analytics capabilities in the world. But what is even more impressive is that they can take this science and translate it into solutions that create real and on-going profit impact for their customers. Their long-standing relationships with leading global companies in a range of sectors attest to this ability.”
Morgan Stanley acted as the exclusive financial advisor to Opera in this transaction.
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