Ayasdi

Ayasdi
Private
Industry Enterprise software
Founded 2008
Headquarters Menlo Park, California
Key people
 Gurjeet Singh
(CEO & Co-Founder)
Gunnar Carlsson
(Co-Founder)
Harlan Sexton
(VP of Research & Co-Founder)
Andy Jacques
(Chief Revenue Officer)
Daniel Druker
(Chief Marketing Officer)
Services Big Data Analytics Machine Learning
Number of employees
 150+ (2016)
Website Ayasdi

Ayasdi is a machine learning and big data analytics software company that offers a machine intelligence software platform and applications to organizations looking to analyze high volume and / 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] fraud detection, trading strategies, customer segmentation, oil & gas well development, drug development, disease research, information security, anomaly detection and national security applications.[2][3]

Ayasdi differs from other machine intelligence and machine learning technologies in that it 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 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 avoids the risk of bias found in other big data analytics approaches since the system in effect 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]

Organizations using Ayasdi have found Ayasdi's automated, platform-based approach to machine intelligence to be two to three orders of magnitude more efficient than traditional approaches to machine learning, as measured in the amount of time and expense required to complete analysis on 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 only 6 person months with Ayasdi.

Ayasdi focuses on applying automation and topology to data analyses in the areas of healthcare, life sciences, oil & gas, public sector, financial services, manufacturing, retail, telecom, etc.[2][3]

History

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 a $30.6 million in series B funding from Institutional Venture Partners (IVP), GE Ventures, and Citi Ventures.[7] On March 25, 2015 Ayasdi announced a new $55M round of Series C funding, led by Kleiner Perkins Caufield & Byers (KPCB), and joined by existing investors, Institutional Venture Partners (IVP), Khosla Ventures, FLOODGATE, Citi Ventures, and new investors, Centerview Capital Technology and Draper Nexus.[8]

Product

Ayasdi is fundamentally 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 at scale at some of the largest corporations and 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 with greatly assist analysts in understanding how data clusters and which variables are relevant. When compared with traditional manual approaches to statistical analysis and machine learning, results with Ayasdi will typically be much faster to achieve and more accurate due to the automation and scalability built into the platform.

Ayasdi also develops machine intelligence applications. One example is Ayasdi Care, which is a suite of cloud-based applications for healthcare providers that is focused on managing and improving patient outcomes, revenue and population health. 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 and billing records.

Ayasdi allows domain experts and data scientists alike to run topological data analysis on big data sets allowing them to find previously unknown insights in big data.[9] Ayasdi has dozens of customers including some of the largest enterprises and governments in the world across industries including healthcare, financial services, oil & gas, financial services, life science, and the public sector.[10][11]

Competitors

Ayasdi competes with a variety of big data analytics and machine learning vendors, most commonly SAS and Palantir from the commercial perspective as well as open source projects like R and Spark. Core competitive differentiation is that Ayasdi's approach is automated, unbiased and hypothesis-free (while other machine learning techniques start with hypotheses), that Ayasdi is a multi-tenant, multi-user scalable computing platform (and not a desktop tool or a programming language) and that Ayasdi is packaged software company (and not a consulting firm.)

References

  1. ↑ "Intermountain to deploy clinical variation management software from Ayasdi". Health Care IT News. 2016-03-02. Retrieved 03/02/2016. Check date values in: |access-date= (help)
  2. 1 2 3 4 "Ayasdi: A Big Data Start-Up With a Long History". The New York Times. 2013-01-16. Retrieved 03/05/2013. Check date values in: |access-date= (help)
  3. 1 2 3 "A cure for cancer? This 'big data' startup says it can deliver". Venturebeat. 2013-01-16. Retrieved 03/05/2013. Check date values in: |access-date= (help)
  4. ↑ "Knowing What’s Possible a Big Obstacle for Big Data". Datanami. 2016-02-01. Retrieved 02/01/2016. Check date values in: |access-date= (help)
  5. ↑ "How a ‘Nuisance Variable’ Turned Into Potential Lifesaver". Datanami. 2016-01-04. Retrieved 01/04/2016. Check date values in: |access-date= (help)
  6. ↑ "Venture capital deals". CNNMoney. 2013-01-16. Retrieved 03/05/2013. Check date values in: |access-date= (help)
  7. ↑ http://www.ayasdi.com/connect/pr-ayasdi-raises-30-million-in-series-b-funding-from-institutional-venture-partners-ge-ventures-and-citi-ventures.html
  8. ↑ http://www.ayasdi.com/company/media/seriesc/
  9. ↑ "Ayasdi Comes Out of Stealth With $10.25M to Anwser Unknown Data Questions". Betakit. 2013-01-16. Retrieved 03/05/2013. Check date values in: |access-date= (help)
  10. ↑ "DARPA-Backed Ayasdi Launches With $10M From Khosla, Floodgate To Uncover The Hidden Value In Big Data". Techcrunch. 2013-01-16. Retrieved 03/05/2013. Check date values in: |access-date= (help)
  11. ↑ "Extracting insights from the shape of complex data using topology". Nature. 2012-09-13. Retrieved 04/01/2013. Check date values in: |access-date= (help)

External links

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