The ClusterAI™ vAppliance

An Unreasonably Simple, Powerful & Cost-Effective Platform for AI & Data Analysis 

The ClusterAI™ vAppliance platform is made up of several discrete components which in combination provide a complete end-to-end big data and artificial intelligence platform. ClusterAI™ uniquely combines the functions of a scalable Enterprise Data Hub (the big data Spark/Hadoop/Kafka etc. processing engine) with an automated data ingestion tool and a selection of Artificial Intelligence algorithms which can be tuned to specific data sources. Since it operates as a standalone, self-contained platform, ClusterAI™ is equally at home in environments new to big data and AI, or in environments where existing deployments already exist.

ClusterAI™ vAppliance Platform Components


Enterprise Data Hub

The Enterprise Hub is the underlying big data engine upon which the ClusterAI™ platform and its various component pieces are supported. The Enterprise Hub is based on  the same powerful & broadly adopted open source technologies that successfully drive big data deployments at the world's largest businesses. The ClusterAI™ Enterprise Hub is a big data platform that hides the underlying open source complexity.


Integrated AppStore

There is an AppStore embedded within the UI of the ClusterAI™ platform. The Appstore provides direct access to thousands of open source and commercial tools and applications which can further enhance the analysis and visualization of data ingested into the platform. The Appstore provides an easy mechanism for searching through the available applications and a point-and-click launch mechanism.

Data Ingestion Engine

DataEnchilada™ is a mechanism for automating ingestion of data from popular on-premise and cloud based data sources such as Oracle, MySQL, Twitter, MixPanel, log files or any others as needed. Static or streaming data is ingested into the ClusterAI™ platform where the embedded artificial intelligence engine will auto-classify incoming streams and immediately make them available for analysis. 

Neural Networks Engine

Various neural network AI algorithms are at the heart of the ClusterAI™ platform. These self-learning algorithms are able to analyze large volumes of streaming data from disparate data sources and make data classification decisions without user input. With additional tuning, each algorithm can be optimized to provide a specific type of feedback from almost any data source.