Ayasdi: Hypothesis-free, Automated Analytics at Scale

Most organizations today are facing tremendous challenges in enhancing the data analytical capabilities due to the continuous and prodigious growth of big data. The information incurred from transactions, sensors, and biometrics has nearly taxed the analytic capabilities of most sophisticated organizations. Inherently, data exhibits complexity, and simplifying it is a crucial step before analysis is carried out. Much of the information consists of underlying properties that characterize various segments and sub-segments from which meaningful insights can be obtained. This is in turn driving computer scientists to examine novel approaches to fasten the capabilities of data analytics platforms. However, this requirement cannot be addressed by the modern day hypothesis-driven analytics, manual machine learning algorithms and statistical tools. "High-performance computers and algorithms can examine big and complex data to seek insights more comprehensively," remarks Gurjeet Singh, CEO, Ayasdi. Envisioning the requirement to find exponential
improvements in analysis and modeling techniques is Ayasdi that helps organizations to analyze highly complex data. "We uncover hidden insights and develop predictive models to automate the business processes with the intelligent applications," delineates Singh.

Ayasdis flagship Machine Intelligence Platform offers its customer organizations to understand data patterns and their relationships in the highly complex data sets through employing automation and Topological Data Analysis(TDA). This technology makes advanced analytics of complex data simple by enabling the analysts to detect subtle patterns that otherwise cannot be captured in other analytics. Using TDA the data scientists, domain experts, are able to identify the geometric relationships between data points, and its clusters. The experts are also able to understand and analyze data without the requirement of writing codes, queries, or asking questions. Once the analysis is completed and insights are derived for a specific business problem, developers can then use Ayasdi platform to create their own intelligent applications.

At its inception, Ayasdi started working for government agencies, one of which was the Food and Drug Administration, then ventured into bioinformatics, pharmaceuticals, and finally healthcare segment. Ayasdi has helped many healthcare providers to analyze crucial information that helped in reducing re-admission rates in hospitals, enabled precision medicine, thus improving the
population heath alongside increasing revenue cycle performance. Further, the firm has also developed a series of "machine intelligence" applications for healthcare and has partnered with sophisticated health systems such as Intermountain Healthcare, Mercy Health System, and Mount Sinai School of Medicine. "We are constantly incorporating new analytical approaches into our frameworks so that they can be combined and synthesized with the existing suite of algorithms," Singh adds.

Citing some instances, Ayasdi through its TDA technology has helped Netherlands Cancer Institute reveal the genetic traits of cancer survivors. The firm also helped Mount Sinai School of Medicine discover six distinct subtypes of Type II Diabetes patients. "Ayasdi aims to make complex data useful for healthcare providers and payers through Machine Intelligence, which represents the next generation of healthcare data analytics," explains Singh."With Ayasdi, healthcare providers can examine millions of patient cases and rapidly ascertain pathways that deliver the highest quality of care, in the most cost-effective manner."

The company has now grown to approximately 100employees and has drawn $100 million in three rounds of venture investment. The functionality of Ayasdi's Machine Intelligent platform and TDA technology in eliminating discrepancies in data mining to enhance productivity and profitability is one the firm's differentiating factors.