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, 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.
Ayasdi focuses on hypothesis-free, automated analytics at scale. 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. Ayasdi then generates mathematical models which are deployed in predictive and operational systems and applications.