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Endor, MIT Spinoff Startup, Raises $5M Seed Round to Break Through AI and Machine Learning Barriers
  • USA - English


News provided by

Endor

Mar 08, 2017, 10:00 ET

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New York, NY (PRWEB) March 08, 2017 -- Endor (http://www.endor.com), a predictive analytics startup based on revolutionary MIT research, today announced the close of its $5M Seed round of financing led by Eric Schmidt's Innovation Endeavors and Marker LLC.

"It’s hard to leverage predictive analytics and quickly iterate on ideas using machine learning. Endor’s platform overcomes these barriers and makes any organization predictive within days" Doron Alter, Co-Founder and CEO, Endor

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Most organizations today aspire to use predictive analytics, artificial intelligence, and machine learning to influence customer behavior and improve business performance. Unfortunately, the process for becoming a “predictive organization” is broken from both a technical and an organizational standpoint. It requires “Unicorns:” Well trained, expensive, rare data scientists and PhDs who are hard to hire and retain. Those teams then invest roughly six months on average cleaning data and building machine learning models, and then have to maintain those models as they degrade over time. Whenever products and consumer behavior change, the models break and need to be re-written. Many of these constraints stem from the inherent limitations of machine learning, which requires too much ‘clean’ data history to be easily applied to noisy data typical of dynamic, ever-changing human behavior.

Endor is the first predictive software platform that lets business users ask any predictive question and get high-quality results in minutes instead of months. It requires no coding, data cleaning, knowledge of machine learning, or PhDs, and far less data history than standard machine learning methods.

Endor’s predictive platform is based on Social Physics: A new science that uses big data to build a predictive, computational theory of human behavior. Social Science originated in MIT through years of groundbreaking research by Prof. Alex Pentland, creator of the MIT Media Lab and one of the world’s most cited scientists, and Dr. Yaniv Altshuler. Endor extended Social Physics using proprietary technology into a powerful engine that is able to explain and predict any human behavior.

“We are coming to realize that human behavior is determined as much by the patterns of our culture as by rational, individual thinking. These patterns can be described mathematically, and used to make accurate predictions,” explained Prof. Pentland. “Endor has taken this new science, Social Physics, expanded upon it, and made it accessible and actionable for any company.”

“We’re seeing the same pain across companies in finance, insurance, retail, and healthcare: It’s hard to leverage predictive analytics and quickly iterate on ideas using machine learning.” said Doron Alter, Co-Founder and CEO, Endor. “Endor’s platform overcomes these barriers and makes any organization predictive within days, facilitating smart data discovery and turning business leaders into ‘Citizen Data Scientists’.”

About Endor
Endor (http://www.endor.com) offers the first predictive software platform that lets business users ask any predictive question, and get high-quality results in minutes. Based on the emerging field of Social Physics developed at MIT, Endor’s new predictive intelligence platform re-invented and automated the process of answering predictive business questions.

About Innovation Endeavors
Innovation Endeavors is an early-stage venture capital firm partnering with startups that apply cutting edge technology to transform large industries. The firm runs a dedicated global team and builds industry networks to create value for its portfolio companies. Innovation Endeavors has offices in Silicon Valley and Tel-Aviv, and is solely backed by Eric Schmidt, the Executive Chairman of Alphabet Inc. Please visit http://www.innovationendeavors.com to learn more.

Doron Alter, Endor, http://www.endor.com, +972 77-461-0085, [email protected]

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