Companies are not extracting value from their customer generated data. It’s hard, because humans are complex behavioral beings. We have a suite of products and algorithms to enable the process of intelligent engagement. Our platform includes leading open source components to enable automated prediction.

Architecture


Figure 1. Example end-to-end view of architecture implementation

The ecosystem.Ai Workbench, Jupyter Notebooks, and API’s are used to manage the entire prediction process. Our unique re-enforcement learning runtime engine is then used to deploy your models, and let them compete with each other to find the best behavioral predictive result. You can deploy the runtime natively on Google Cloud, Microsoft Azure and AWS.