In the age of rapid evolution of AI-related technologies, channel applications, e.g., web, kiosk, IVR, etc., are becoming increasingly intelligent where industries are developing strategies to scale the initial experimentations to scaled implementation resolving data quality, governance, and responsible AI challenges. Nonetheless, there is continuous effort put into moving past these inhibitors and scaling the implementations. 

Let’s take an example of a channel application that supports foundation customer services. In the traditional architectural approach, the application would consume several APIs exposed by the enterprise with different types, e.g., experience and process APIs, to render the services. More often, in an orchestrated information fetch, this approach has resulted in significant chattiness, network overheads, and performance (e.g., response time) issues.