Ayasdi

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Ayasdi

Type	Private
Industry	Enterprise software
Founded	2008
Headquarters	Menlo Park, California
Key people	Simon Moss (CEO) Stephen Moody (CIO) Warren Zafrin (VP of Engineering) Chris Kacerguis (Architecture Director)
Services	Big Data Analytics Machine Learning
Number of employees	65 (2020)
Website	Ayasdi

Ayasdi began as a machine intelligence software company in 2008 that developed a software application 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 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.^{[citation needed]}

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] In May 2019, Ayasdi joined the SymphonyAI portfolio. This billion dollar investment platform is focused on developing the next generation of artificial intelligence and machine learning companies in Healthcare, Financial Services, Retail, Industrial, Media and Enterprise markets. The company is renamed Symphony AyasdiAI.^[9]

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.^[10]

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.^[11]

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[]

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At it's core, SensaAML™^[12] is designed to empower investigators with a dynamic and deep analytical fidelity to identify and report on truly suspicious and high-risk behaviors in their customer activity. The platform ingests data from customers, counterparties, and transactions and filters it through our proprietary machine learning system to create data segments. Segmentation assignments are based on the behavior of data inputs and then reassigned based on transactions and their myriad relationships over time. The result is an agile understanding of data and its relationship to its sources. In addition, this technique quickly identifies potentially malicious data attributes and automatically creates new, derived attributes to accelerate intelligent segmentation.  

The SensaAML™^[13] application is cloud-enabled, thus eliminating the requirement for on-prem deployment, and was designed to be flexible and adaptable to facilitate existing TMS configurations.

Users and industries[]

Ayasdi customers include many large Financial Institutions^[14] with a global footprint, who are seen as early adopters and innovators in their field. These organizations are leading the way in the adoption of Artificial Intelligence and machine-learning for its efficacy in the discovery of financial crime and high-risk behaviors that indicate money-laundering activities.^[15][16]

References[]

External links[]

• Ayasdi founders and investor lecture and discussion with entrepreneurship students, Stanford Entrepreneurship Corner, 2014.02.05