Angoss adds Real-Time Analytics Capability
Angoss real-time scoring cloud service delivers intelligent, real-time scores or recommendations, and integrates with operational systems.
TORONTO, March 26, 2013 /CNW/ - Angoss Software Corporation (Angoss) announced the addition of real-time scoring as a powerful cloud service that delivers intelligent, real-time scores or recommendations for businesses looking to embed predictive analytics into business operations.
The real-time scoring cloud service integrates with any operational system to provide on-demand scores, decisions models or recommendations as well as apply real-time strategic actions or treatments. It allows for ease of use in both applying models in real-time and updating models as new information develops.
The cloud service both deploys and manages predictive models built in Angoss KnowledgeSTUDIO™ or other popular statistical programs such as R and SAS® through Predictive Model Markup Language (PMML). Organizations also gain efficiencies by deploying Strategy Tree treatments in real-time with Angoss StrategyBUILDER™.
Real-Time Scoring in Action
Angoss' real-time scoring cloud service can be used for online product recommendations, targeted marketing treatments, cross sell and up-sell opportunities, credit fraud detection and loss, and next sales activity, among others.
Key Features: Real-Time Scoring
- API support for SOAP, REST and XML/JSON allows for simple integration with any operational systems such as line of business applications, customer relationship management, call center systems, website etcetera.
- Flexible, standard model deployment includes the ability to deploy Angoss KnowledgeSTUDIO models, or models developed in other statistical programs such as R and SAS via PMML.
- Advanced model support includes the most popular models: Logistic Regression, Linear Regression, Decision Trees, Strategy Trees, Market Basket Analysis, Scorecards, Neural Networks and Cluster Analysis.
- Centralized, remote model management and deployment lowers upfront IT infrastructure costs and demand on internal resources.