Home News Crowdsourcing app Findyr merges with Analytics and Machine Learning Experts Leviathan

Crowdsourcing app Findyr merges with Analytics and Machine Learning Experts Leviathan

US: Findyr, the global platform for crowdsourcing of hyperlocal, street-level data and insights has today announced its merger with Leviathan, the big data analytics platform specializing in analysis of cloud ingested big data with leading machine learning models. The merger, which will continue to operate as Findyr, is seeking to solve some of the biggest location-based challenges being faced across the globe by the private and public sectors.

Answering the growing challenges in geo-location intelligence service offerings, which until now have relied on low-frequency satellite imagery, Findyr will be creating around the clock real-time location-based data access to critical information.

Lyndon Oh, founder of Leviathan and newly appointed CEO of Findyr, commented: “Our on-demand crowdsourced data collection platform and real-time geospatial data feed creates the world’s most complete high-frequency data map for any location in the world. By joining forces, our ground-level data capture and cloud-based machine learning tools offer enterprises unprecedented precision and a unique advantage in analyzing physical assets, hedging against downside risks in human behavior, and spotting economic opportunity from one city block to the next.”

Before becoming CEO of Findyr, Lyndon was the founder and CEO of Leviathan Analytics, the New York-based software provider selling location analytics tools to customers in the hospitality, industrial goods, security and advisory service markets. Before founding Leviathan, Lyndon was a program manager at Google and prior to that was an executive in analytics at Facebook. He also holds a Ph.D. from the University of St. Gallen in Switzerland and an M.Sc. from the London School of Economics.

Since its launch, Findyr has been disrupting traditional models of location-based data collection with its unique crowdsourced tasking capabilities and global community of data collectors providing high-frequency, accurate intelligence for customers seeking near real-time, accurate observational data.

Findyr is working with blue-chip clients including Gallup, the world’s leading analytics and consultancy practice, best known for its World Poll surveys researching “100 crucial issues” from business and economics to citizen-engagement, education, family life, communications, health and much more. Working with Findyr’s highly trained and global community, Gallup and other customers are now able to crowdsource accurate data collection, displacing traditional time intensive and costly practices of location-based data collection.

Findyr is owned and operated by Granahan McCourt Capital, the worldwide investors in technology, media and telecommunications, founded by David C. McCourt, one of the world’s most successful entrepreneurs.

David McCourt, founder and CEO of Granahan McCourt Capital, said: “We are excited to be creating a new era of location data services as Findyr and Leviathan combine their expertise and unique market offerings. Findyr has an established and fast-growing customer base who are looking to solve hugely significant global challenges and by adding Leviathan’s expertise, we are building the most sophisticated machine learning platform so that customers seeking benefits from location-based data can get the intelligence and insight they desperately need. By solving incomplete cloud datasets which other machine learning vendors base their models on, this is an unrivaled solution.

“Findyr has started a revolution based on its commitment to insight and innovation by empowering its sophisticated, reliable crowdsourced data from highly trained community members with world-leading analytical capabilities, allowing us to provide an incredibly detailed and ever-more accurate picture of the important matters facing people and businesses in every area of the globe.

“We are now the leader in taking low frequency but critical information and making it near real-time, which provides the answer for anyone who relies on making decisions on this insight.”