Skytree has developed a system that can help organizations discover deep analytic insight of their available data. The machine learning platform can predict trends, make recommendations and reveal untapped markets and customer based on the available data. Machine learning goes much further then general business intelligence.

With business intelligence users still need to know which questions to ask to make information out of the data. With Machine Learning this is not necessary anymore as machine learning covers predictive analysis, data mining pattern recognition, similarity search, outlier detection and recommendation systems. It can come up with patterns you would not have thought about before.

The goal of Skytree is to bring machine learning to the mainstream. They have developed a product called Skytree Server, which is a general-purpose scalable machine learning system. The Skytree Server can be easily connected and configured to existing IT infrastructure.

According to Skytree “it can accept data streams from multiple sources and compute near-instantaneous results on each one”. The algorithms of the Machine Learning allow scalability and processing the big data at high speed. Machine Learning is used by a lot of companies to analyse huge amounts of specific data.

The technology of Skytree however can analyse any type of data. It can perform similarity search such as used in Shazam, it can provide extensive recommendation to the level of recommendations based on combinations of previous purchases, discussions on social media, search path on a website, historical searches etc. With machine learning the system is improved over time. The more data is fed into the system, the better the system know how to process the data and the better insights can be found.

With so much data available in your company and this data becoming more every data it becomes increasingly difficult to ask the right questions about your data. With Skytree these questions are not necessary anymore as with Machine Learning you find answers to questions you were not able to ask. This really turns big data into information and into knowledge and this can help companies make better decisions.



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Head Office

1731 Technology Drive, Suite 700
San Jose
United States

Countries Supported

United States


Education and research, Financial Services, Public sector and governments, Retail

Size of Customers


Year Founded

December 2010


Funding Received from Investors

$21.6 Million


Alireza Masrour, In-Q-Tel, Javelin Venture Partners, Osage University Partners, Plug & Play Ventures, Scott McNealy, United Parcel Service, US Venture Partners

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