Use Cases By Industry

Banks are using machine learning to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from risk analysis and fraud detection to marketing, in order to make data-driven decisions that lead to increased profitability.

Credit Card Processing companies are aggregating credit card transaction data, often held in multiple and difficult to access systems, in a modern data warehouse; and the leverage machine learning to identify patterns and trends in their datasets and to enable high-value predictions in guiding better decisions and smarter actions in near real time and without human intervention.

Energy companies are using machine learning to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from inventory management to marketing, in order to make data-driven decisions that lead to increased profitability.

FinTech companies are using machine learning to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from risk analysis and portfolio optimization to marketing, in order to make data-driven decisions that lead to increased profitability.

Healthcare companies are using machine learning to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from readmission risk and occupancy rates to marketing, in order to make data-driven decisions that lead to increased profitability.

Insurance companies are using machine learning to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from underwriting to marketing in order to make data-driven decisions to lead to increased profitability.

Marketing departments and organizations are using machine learning to determine the effectiveness of their marketing activities and operations, accurately target customers, move them further down the funnel toward purchase, and improve customer relationships. Machine learning allows marketers in every industry to accurately determine and improve ROI, resulting in tangible bottom-line value.

Across the government, leaders are challenged every day to balance the public’s need for services with the directive to do more with less. Success at every agency hinges on the ability to deliver insights from data quickly. Providing services in this environment requires fast and accurate predictions.

As the International Maritime Organization continues to apply more stringent regulation on energy efficiency to support the demand for ever greener and cleaner shipping, ship owners and ship management companies urgently need to deploy IoT devices, a modern platform for capturing, storing and organizing their data, then layer Analytics and Automated Machine Learning to enable high-value predictions in guiding better decisions and smarter actions in near real time and without human intervention.

As traditional revenues continue to fall, telecoms enterprises are looking to leverage data. Anonymized information from mobile devices provide insights into how people use the mobile web, which sites they visit, what they buy and where they go; valuable information that is marketable to retailers, property specialists, the transport and travel industries and the public sector. Underpinning existing systems with a modern data centric platform for capturing, curating, storing and organizing their data, then layering Analytics and Automated Machine Learning will enable high-value predictions in guiding better decisions and smarter actions in near real time and build value without human intervention.