The Rec-E™ solution is a collection of intelligent algorithm codebase covers; Decision Tree, Regression, Neural Network – Convolution & Recurrent, Graph Processing, Clustering & Deep Learning Self Organizing Maps Deep Neural Network. Rec-E™ provides flexibility to be adapted for various use cases and applications. The algorithm covers a wide array of complexity of data (text, images, voice, sensors) and its format that one should expect to deliver closest recommendation for action. The algorithm reads and analyze the complex patterns in real-time, score the outcomes & deliver contextual recommendations while at the same time have the capability to analyze the historical transactional & interactional behavior across variety of channels and systems.
Rec-E™ provides flexibility to work with tools like R, Python and many other open source tool. It is flexible to work with any database, data warehouse, data lake or small data marts. It can also interact directly with operational systems.