The microservice that combines the price recommender (optimization, dynamic pricing) and the expected revenue/turnover (demand forecasting, elasticity, etc.)
ELEKS Analytical Suite IS a composition of machine learning and optimization solutions that works as an integral whole toward Cost Optimization, Utility Maximization, and Profit Maximization objectives. STANDS on the premises of big data, real-time stream processing, and machine learning to analyze heterogeneous data from different sources. INCORPORATES three customer-side models to introduce control over the customer decision journey e.g., for retail: Recommender System, Dynamic Pricing, Customer Segmentation; and three planning models to support operations management and cost centers: Demand Prediction, Capacity Planning, Logistics. The first and most valued part here is the forecasting and dynamic pricing, that is built using the SOTA ML estimators, available in Azure ML Studio (even with visual, easy to use, blocks). All data and logic flow can be covered by the SageMaker and then efficiently deployed by the Azure endpoints (Azure ML CLI) or MLFlow, also with Azure Monitor, if needed. ALLOWS modularity: an existing model or solution can be equally integrated into the Suite thanks to well-thought-out system architecture.