Harnessing & Analyzing Data at Scale is Tough

Here's How Our Platform Fixes That

Data Sources

The Cardinality platform has a large and growing library of collectors that can take input from all kinds of on-prem and cloud data sources - including sensor data, operational data, billing data, data warehouse data, and more.

DataOps Engine

The DataOps Engine is a cloud-native data integration and virtualization engine that manages the ingestion of data from a diversity of sources, preparing and making the data available to be analyzed in-memory or written to storage for historical analytics.

The DataOps Engine excels at real-time data ingestion. Capable of streaming over 50 billion events in a day, the DataOps Engine unlocks the potential of IoT across countless use cases from autonomous and connected vehicles to robotics, Industry 4.0, next-generation supply chains, cross-industry drone applications, smart cities, healthcare and agriculture. And, in hybrid cloud environments, the DataOps Engine enables the efficient movement and virtualization of data from the edge to the on-premises datacenter to the cloud.

Use Case Engine

The Use Case Engine makes it incredibly easy to develop use cases that deliver amazing business outcomes. The Use Case Engine is cloud-native, allowing you to perform real-time and historical analytics at the edge, in on-premises data centers, and in the cloud. Born and bred in the highly complex world of telecom, the Use Case Engine is powering award-winning AI solutions and continent-spanning deployments in some of the most demanding environments imaginable.

With the Use Case Engine, you can easily create analytics solutions with little to no code, using an intuitive graphical user interface. Our Use Case Engine’s open design lets you choose your favorite tools at every point of the data pipeline — from data ingestion to storage, analytics, dashboards, visualization, reporting, and machine learning.


Send the results of your analytics to your choice of reports, dashboards or visualization tools, to upstream applications, and to machine learning studios.