Confused about which technology vendor to use for your business problem? Ask for help

Confused about which technology vendor to use for your business problem? Ask for help

    • AYASDI
    • www.ayasdi.com/
    • 201-500 Employees

Ayasdi helps companies around the world to use Artificial Intelligence and Big Data to make employees hundreds of times more productive and to drive fundamental breakthroughs that are beyond the capabilities of humans.
Ayasdi’s revolutionary machine intelligence platform leverages automation, machine learning and topological data analysis to simplify the extraction of knowledge from even the largest and most complex data sets and to facilitate the deployment of intelligent, AI-based applications across the enterprise.

Developed by Stanford computational mathematicians, Ayasdi’s unique approach to machine intelligence leverages breakthrough mathematics, highly automated software and inexpensive, scalable computers to revolutionize the process of converting big data into business insight.

Headquartered: Menlo Park, CA

Case Studies (1)

Title: Bank Reduces Money-Laundering Investigation Effort with AI Client Company: AYASDI Executive Summary:

Ayasdi claims to have unearthed many new cases and patterns directly correlated to fraud – as well as reducing HSBC’s false positives (cases when HSBC’s existing rules would have flagged for laundering risk when no such risk actually existed).

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Executive Interviews (1)

Interviewee Name: Sangeeta Chakraborty

Company Role: Chief Customer Officer

Interview Summary: In this episode we speak with Sangeeta Chakraborty Chief Customer Officer at Ayasdi and discuss the applications of data science and AI in healthcare, what hospitals and healthcare systems are doing to adopt this kind of technology, and how this approach can be extended to other forms of enterprise. This interview was conducted in-person at BoostrapLabs annual AI conference in SF. It’s easy to see how Facebook and Google or the best-funded Bay Area start-up are leveraging artificial intelligence, but what about industries that are often resistant to cutting edge technology? How are they adjusting the ways they are doing business to stay competitive with data science and AI, particularly in areas where sooner or later they will really have to adapt in order to stay in business? That's what we set out to ask in this week's exclusive interview.

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Mentions on TechEmergence(3)

Machine Learning in Genomics - Current Efforts and Future Applications

Genomics is a branch of molecular biology focused on studying all aspects of a genome, or the complete set of genes within a particular organism. Today, machine learning is playing an integral role in the evolution of the field of genomics. We set out in this article to examine the applications of machine learning in genomics to help business le...

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Machine Learning Healthcare Applications - 2018 and Beyond

In the broad sweep of AI's current worldly ambitions, machine learning healthcare applications seem to top the list for funding and press in the last three years. Since early 2013, IBM's Watson has been used in the medical field, and after winning an astounding series of games against with world's best living Go player, Google DeepMind's team d...

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Artificial Intelligence Industry – An Overview by Segment

Today's artificial intelligence market is not easy to quantify. Besides the lack of consensus on a coherent definition for "artificial intelligence" as a term, the field's nascent stage of development makes it difficult to carve out silos or hard barriers of where one industry or application ends, and another begins. In one of our more popular ...

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