Causality cannot be proven from observational data. However, with comprehensive data, you can get close to proof. The more comprehensive your data, the lower the risk of misinterpreting correlation as causation. Comprehensive data involves a multi-layered data model.

Our ObjectAnalytics Database is designed to store complex data, such as millions of patients with billions of events (diagnoses, prescriptions, genomic data, etc.). Our Causal Discovery algorithms utilize this object-oriented data storage to efficiently search for direct and indirect explanations for a target event, uncovering potential cause-and-effect relationships.

White paper: Von Korrelation über Kausalität zu künstlicher Intelligenz

Download our
White Paper: “From
Correlation to
Causation to AI”

Download

We offer industry-specific,
annual license models to meet your needs.

Request License Quote
computer icon

Are you a Data Scientist and tired of SQL for analytics?

Why not develop next generation intelligent algorithms by operating on entire objects instead of tables, rows, and columns?

Learn more »
icon

Are you an Application Developer and feel hampered by clumsy backends?

Unleash your creativity to build analytical applications with whole objects at your fingertips!

Learn more »
icon

As a Business Analyst, do you have endless data but feel lost in myriads of correlations?

Easily understand causation beyond correlation, based on a holistic view of your business objects.

Learn more »