Investment to expand North American operations and meet surging demand for Cherre’s advanced real-time data and analytics platform
NEW YORK, Oct. 1, 2018 /PRNewswire/ — Cherre, a real estate data platform, today announced that it has closed a $9 million seed funding round led by Navitas Capital. Cherre provides large enterprises, insurance companies, banks and investors with a platform to collect, augment, and resolve property data in real-time from thousands of public, private, and internal sources, allowing them to evaluate investment and underwriting opportunities more accurately and efficiently than ever before.
“In less than a year since formally launching its platform, Cherre has already revolutionized the way financial institutions, insurance companies, real estate brokerages and other large businesses process and analyze massive stores of data every day,” said Navitas Capital Managing Partner Jim Pettit. “With the backing of Navitas and other investors, the platform will be in pole position to bring its streamlined real estate data services to an exponentially growing roster of clients.”
In addition to Navitas Capital, the funding round was also joined by Carthona Capital, iLOOKABOUT, Dreamit Ventures, and Red Swan Ventures. Notable pre-seed investors in Cherre include Recursive Ventures, Sarona Ventures, Wharton Angel Group, Harvard Angel Group, New York Angels and Angel Investor Forum.
Founded in 2016, Cherre is a data platform that collects and integrates thousands of disparate data feeds in the notoriously fragmented and unreliable real estate market. Modeled after high-frequency trading platforms, artificial intelligence-powered platform allows companies to connect and resolve all of their internal and external data to Cherre’s platform, which includes a vast range of data objects and other verified information. Through access to Cherre, companies are instantly provided with clean, accurate and up-to-date information such as property history, demographics and market comparisons to be used in advanced analytics and power better decision-making, while saving millions of dollars in manual data collection and analysis costs.
Funding from the round will be devoted toward meeting the surging demand for service from Cherre’s existing clients, as well as expanding operations throughout the U.S. and Canada.
Cherre’s platform has experienced significant growth since its formal launch in December 2017, attracting high-profile clients including The Real Estate Board of NY (REBNY), Keller Williams NYC, Stratus Data Systems, August Partners, Platinum Properties, the largest property and casualty insurance company in the world and various other Fortune 500 companies.
“Many of the world’s biggest industries are increasingly looking to harness the power of real-time data and to reevaluate their use of data in their core business functions,” said Cherre CEO L.D. Salmanson. “Cherre has seen an incredible adoption rate from financial institutions, insurance companies, real estate investment groups and brokerages, and dozens of other large corporations. With a new group of investors now on board, we are poised to take our platform and data insights to even more companies looking to take their business to the next level.”
About Cherre
Cherre is a leading real estate data platform that allows large enterprises, insurance companies, banks and investors to collect, augment, and resolve property data from thousands of public, private, and internal sources in real-time. Its mission is to empower its clients to evaluate investment and underwriting opportunities faster and more accurately through its one-of-a-kind, artificial intelligence-powered platform. Founded in 2016, Cherre has already been adopted by leading companies including The Real Estate Board of NY (REBNY), Keller Williams NYC, Stratus Data Systems, August Partners, Platinum Properties, the largest property and casualty insurance company in the world and various other Fortune 500 companies. The company is headquartered in New York City. For more information, visit cherre.com.
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