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The Version-9.6 of Angoss Software Suite Released

By CIOReview | Monday, April 25, 2016
Rick Makos, President and CEO, Angoss

Rick Makos, President and CEO, Angoss

FREMONT, CA: Angoss Software recently announced the release of its version 9.6 platform. The latest version 9.6 features additions that augment the current Angoss Data Science platform offering, and enables enhanced business performances.

Angoss’ newest platform also includes enhancements to current KnowledgeSEEKER, KnowledgeSTUDIO, KnowledgeREADER, and InsightOPTIMIZER products. Angoss has also improved its data integration, advanced modeling, model evaluation, and documentation automation to supply analysts with a complete toolset for end-to-end superior scorecard development functionality.

“Our aim is to consistently improve the user experience through our business centric product enhancements,” said Rick Makos, President and CEO, Angoss. “The advancements we have made to our software functionality truly enable us to offer customer solutions that contribute to significant efficiency gains, expand optimization possibilities, and generate faster results via customizable methods.”

Angoss’ in-database driver allows users to deploy predictive models directly within the appliance and unlock the value of big data. The company’s tools are designed to provide customers with an easy to use, end to end predictive analytics platform, with features like drag and drop functionality and automatic code generation. Angoss also has the capability to integrate with multiple data sources and uses both structured and unstructured data, through a single data acquisition interface.

“Angoss prides itself on bridging the gap between data science and business users, and our end to end capability encompasses data acquisition, data preparation, and comprehensive modeling,” said Bill Sheldon, Chief Solutions Officer, Angoss. “Through our professional services we help clients quickly translate business issues into predictive models by providing our own subject matter expertise and experienced data scientists for training, knowledge transfer, and mentoring.”