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Big Data Journal: Article

Big Data Machine Learning Start-Up Gets $30.8 Million

Its approach combines advanced machine learning techniques with a branch of mathematics called Topological Data Analysis (TDA)

Five-year-old Big Data start-up Ayasdi, out only six months, has gotten B round funding worth $30.6 million led by Institutional Venture Partners (IVP) with newcomers GE Ventures and Citi Ventures kicking in as well as existing investors Khosla Ventures and Floodgate participating.

That makes at least $42.6 altogether.

IVP gets a board seat.

Ayasdi's built what it calls an Insight Discovery platform designed for domain experts and business people who are supposed to use it to automatically derive insights from complex data and "operationalize" them to help enterprises solve difficult and expensive problems.

According to GE it can find a "needle in a haystack."

Its approach combines advanced machine learning techniques with a branch of mathematics called Topological Data Analysis (TDA) to discover insights without coding, scripting or querying manually.

The technology also uses a bunch of best-of-breed algorithms to automatically map both structured and unstructured datasets and provide the most relevant and statistically valid insights.

Ayasdi's customers and collaborators include General Electric, Citigroup, Merck, Anadarko, the US Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), the University of California at San Francisco (UCSF), Mount Sinai Hospital, Texas A&M University and Harvard Medical School.

The widgetry is supposed to save organizations from having to build a Big Data infrastructure and employ large teams of highly trained data scientists who typically spend months, sometimes years, asking questions of data that are fraught with human assumptions and biases to find breakthrough insights.

The company claims "the probability of discovering these insights is low because there are too many questions to ask and not enough data scientists to ask them. Once found, deploying solutions to help enterprises solve critical problems can further lengthen the process."

Instead Ayasdi is supposed to abstract away complexity and make powerful machine learning tools accessible to ordinary business users.

The new funding is earmarked for further R&D, continued automation, enhancing operational workflow capabilities for integrating Ayasdi into core enterprise IT environments and real-time business operations and access to pre-loaded public datasets.

The start-up also means to double its size in the next 12 months and create versions of the technology for each vertical.

It says its widgetry is being used to discover new drug therapies, uncover the causes of diseases, root out financial fraud and the possibility of terrorist attacks, accelerate more accurate energy exploration and discover customer segmentation.

Its platform is engineered to complement other Big Data solutions like Cloudera's Apache Hadoop.

Ayaski, which means "to seek" in Cherokee, was started in 2008 after a decade of research at Stanford, DARPA and NSF by co-founders Stanford professor Gunnar Carlsson and Gurjeet Singh, a PhD mathematics student, now the start-up's CEO.

More Stories By Maureen O'Gara

Maureen O'Gara the most read technology reporter for the past 20 years, is the Cloud Computing and Virtualization News Desk editor of SYS-CON Media. She is the publisher of famous "Billygrams" and the editor-in-chief of "Client/Server News" for more than a decade. One of the most respected technology reporters in the business, Maureen can be reached by email at maureen(at)sys-con.com or paperboy(at)g2news.com, and by phone at 516 759-7025. Twitter: @MaureenOGara

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