quickly build and deploy an engine as a web service on production with customizable templates;
respond to dynamic queries in real-time once deployed as a web service;
evaluate and tune multiple engine variants systematically;
unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics;
speed up machine learning modeling with systematic processes and pre-built evaluation measures;
support machine learning and data processing libraries such as Spark MLLib and OpenNLP;
implement your own machine learning models and seamlessly incorporate them into your engine;
simplify data infrastructure management.