No bank wants its valuable customers to churn. Retaining customers with customer churn prediction is the most cost-effective way to bring in revenue.
Retailers can proactively plan retail inventory needs with supply and demand forecasting using the AI & Analytics Engine.
Insurers can leverage AI/ML and stay competitive by switching to a dynamic policy pricing strategy with the AI & Analytics Engine.
Using the AI & Analytics Engine, companies in the financial services industry can improve the speed and accuracy of fraud detection with Machine...
Facility optimization to maximize energy efficiency is a challenging concern. ML can be applied to AI-enabled BMS systems and facility management...
Price optimization is becoming increasingly important as a significant driver of competitive advantage for today's retailers. Leverage AI price...
The AI & Analytics Engine optimized and productionized predictive maintenance strategies, for mission-critical assets so they ran reliably &...
The AI & Analytics Engine helps physical space optimization projects be developed, providing decision-makers with rich insights to best utilize space.
In this article, we look at the use of AI in trading, in the finance industry. PI.EXCHANGE built a predictive model to quantify the risks and returns...
By leveraging the highly scalable automation and technology available within their AI & Analytics Engine, firms can leverage AI for cybersecurity.
A use case for AI in logistics: The AI & Analytics Engine predicted regional trade-flow of competitors in useful time horizons for a trading company.
Predicting fluctuations in global shipment volumes for demand forecasting with machine learning.