Build Self-Learning Predictive Apps with New Predictive Cloud

Posted 9/28/2015 2:02:16 PM by STUART PARKERSON, Publisher Emeritus

Build Self-Learning Predictive Apps with New Predictive Cloud has launched the Predictive Cloud, an open cloud based platform that enables developers to build predictive apps. Powered by a self-learning predictive engine, the Predictive Cloud taps into the intelligence gathered from analyzing nearly 100 billion interactions. expects the Predictive Cloud to be used in a number of instances including:

- Predictive-as-a-Platform: Through the Predictive Cloud Open API, independent software vendors (ISVs) can tap into the Predictive Cloud to add predictive functionality into their own apps.

- Predictive-as-a-Service: Companies can leverage the Predictive Cloud to scale revenue and improve internal processes and operations.

- Sales Acceleration Apps: Impact sales through sales communications, email and web tracking, predictive forecasting, lead and opportunity scoring, sales gamification, and sales hiring. 

“The vision for the Predictive Cloud dates back to the founding of the company in 2004,” said Dave Elkington, founder and CEO, “We are building an Amazon-style recommendation engine for business – a system capable of intelligently analyzing billions of data points in real-time and recommending the optimal next steps for almost any application or business process. This lays the groundwork for a future where predictive technology can be applied not just to sales organizations, but also to government, healthcare, retail and beyond.”

The Predictive Cloud is powered by’s Neuralytics engine, a real-time, self-learning predictive engine that incorporates advanced learning algorithms to analyze data and provide intelligent recommendations. 

This self-learning capability means that all transactions are automatically captured and continuously refreshed, providing a tight feedback model between actions and results to enhance the predictive power of the system. Data from the Predictive Cloud is combined with anonymized customer data, then correlated and enriched with external data sources, creating “High Definition” Data to increase predictive accuracy.

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About the author: STUART PARKERSON, Publisher Emeritus

Stuart Parkerson has an extensive background in niche technology publishing.

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