Ayasdi

Ayasdi is a machine intelligence software company that offers a software platform and applications to organizations looking to analyze and build predictive models using big data or highly dimensional data sets. Organizations and governments have deployed Ayasdi's software across a variety of use cases including the development of clinical pathways for hospitals,[1] anti-money laundering, fraud detection, trading strategies, customer segmentation, oil and gas well development, drug development, disease research, information security, anomaly detection, and national security applications.[2][3]

Ayasdi
TypePrivate
IndustryEnterprise software
Founded2008
HeadquartersMenlo Park, California
Key people
  • Simon Moss
  • (CEO)
  • Stephen Moody
  • (CIO)
  • Warren Zafrin
  • (VP of Engineering)
  • Chris Kacerguis
  • (Architecture Director)
ServicesBig Data Analytics Machine Learning
Number of employees
65 (2020)
WebsiteAyasdi

Ayasdi focuses on hypothesis-free, automated analytics at scale.[4] In effect, the Ayasdi system consumes the target data set, runs many different unsupervised and supervised machine learning algorithms on the data, automatically finds and ranks best fits, and then applies topological data analysis to find similar groups within the resultant data. It presents the end analysis in the form of a network similarity map, which is useful for an analyst to use to further explore the groupings and correlations that the system has uncovered. This reduces the risk of bias since the system surfaces "what the data says" in an unbiased fashion, rather than relying on analysts or data scientists manually running algorithms in support of pre-existing hypotheses.[5] Ayasdi then generates mathematical models which are deployed in predictive and operational systems and applications.

Organizations using Ayasdi have found Ayasdi's automated, platform-based approach to machine intelligence to be two to five orders of magnitude more efficient than existing approaches to big data analytics, as measured in the amount of time and expense required to complete analysis and build models using large and complex data sets. One widely reported example at a top five global systemically important bank was that to build models required for the annual Comprehensive Capital Analysis and Review (CCAR) process took 1,800 person-months with traditional manual big data analytics and machine learning tools, but took 6 person-months with Ayasdi. A project at a second global systemically important bank showed Ayasdi reducing the time to build risk models from 3,000 person-hours to 10 minutes.

History and funding

Ayasdi was founded in 2008 by Gunnar Carlsson, Gurjeet Singh, and Harlan Sexton after 12 years of research and development at Stanford University.[2][3] While at Stanford, the founders received $1.25 million in DARPA and IARPA grants for "high-risk, high-payoff research".[2] In 2012 Ayasdi landed a Series A round of funding led by Floodgate Capital and Khosla Ventures for $10.25 million.[6] On July 16, 2013, Ayasdi closed $30.6 million in Series B funding from Institutional Venture Partners, GE Ventures, and Citi Ventures.[7] On March 25, 2015, Ayasdi announced a new $55 million round of Series C funding, led by Kleiner Perkins Caufield & Byers, and joined by four current investors, Institutional Venture Partners, Khosla Ventures, Floodgate Capital, Citi Ventures, and two new investors, Centerview Capital Technology and Draper Nexus.[8]

Product

Ayasdi is a machine intelligence platform. It includes dozens of statistical and both supervised and unsupervised machine learning algorithms and can be extended to include whatever algorithms are required for a particular class of analysis. The platform is extensively automated and is in production at scale at many global 100 companies and at governments in the world. It features Topological Data Analysis as a unifying analytical framework, which automatically calculates groupings and similarity across large and highly dimensional data sets, generating network maps which greatly assist analysts in understanding how data clusters and which variables are relevant. When compared with manual approaches to statistical analysis and machine learning, results with Ayasdi will typically be achieved much faster to achieve and more accurate due to the automation and scalability built into the platform. The Ayasdi platform also develops mathematical models, including predictive models, based on the results of the analysis. This allows Ayasdi to deployed as an operational system, or as a part of operational systems, and not just for analysis.[9]

In 2013, The Economist deployed Ayasdi's topological data analysis software to identify "value" players in the English Premier League and allow online readers to select their own teams to compete with the 2012-2013 season champions, Manchester United.[10]

Ayasdi can be deployed on-premises using Intel-based servers, or on either public or private cloud infrastructure. The platform runs on Linux and Hadoop.

Applications

Ayasdi also develops machine intelligence applications. One example is Ayasdi Care, a suite of cloud-based applications for healthcare providers focused on managing and improving patient outcomes by identifying more efficient care strategies for doctors and hospitals.[11] For example, Ayasdi clinical variation, one of the applications in Ayasdi Care, automatically discovers the ideal care paths for medical procedures based on analyzing historical patient data, billing records and insurance claims.[12]

Users and industries

Ayasdi customers include many large enterprises, medical research institutions and governments across industries including health care, financial services, oil and gas, security, life sciences, and the public sector.[13][14]

References
  1. "Intermountain to deploy clinical variation management software from Ayasdi". Health Care IT News. March 2, 2016. Retrieved March 2, 2016.
  2. "Ayasdi: A Big Data Start-Up With a Long History". The New York Times. January 16, 2013. Retrieved March 5, 2013.
  3. "A cure for cancer? This 'big data' startup says it can deliver". Venturebeat. January 16, 2013. Retrieved March 5, 2013.
  4. "Knowing What's Possible a Big Obstacle for Big Data". Datanami. February 1, 2016. Retrieved February 1, 2016.
  5. "How a 'Nuisance Variable' Turned Into Potential Lifesaver". Datanami. January 4, 2016. Retrieved January 4, 2016.
  6. "Venture capital deals". CNNMoney. January 16, 2013. Archived from the original on 2013-03-12. Retrieved March 5, 2013.
  7. "News and Events - Ayasdi". Ayasdi.com. Retrieved July 3, 2017.
  8. "News and Events - Ayasdi". Ayasdi.com. Retrieved July 3, 2017.
  9. Erin Bury (January 16, 2013). "BetaKit ยป Ayasdi Comes Out of Stealth With $10.25M to Answer Unknown Data Questions". Betakit. Archived from the original on 2013-03-08. Retrieved July 3, 2017.
  10. "Fantasy football manager". The Economist. 2013-08-16. ISSN 0013-0613. Retrieved 2019-02-26.
  11. "Ayasdi uses topological data analysis to find best care paths". SearchHealthIT. Retrieved 2019-02-26.
  12. "Machine intelligence pushes customized data analysis to health systems". Modern Healthcare. Retrieved 2019-02-26.
  13. "DARPA-Backed Ayasdi Launches With $10M From Khosla, Floodgate To Uncover The Hidden Value In Big Data". Techcrunch. January 16, 2013. Retrieved March 5, 2013.
  14. "Extracting insights from the shape of complex data using topology". Nature. September 13, 2012. Retrieved April 1, 2013.
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