As a follow up to queries with regard to “how is the contentAI platform different?” – The basics are that the contentAI platform converges conversational AI (Natural Language Processing “NLP”), machine learning, pattern recognition, session management and personalization with a “STORY STRUCTURE.”
“Story” means that we start at “A” and end at “Z.” The path through may be non-linear, but, the User is guided to progress through the engagement and reach one (often of many) possible endings.
For mobile Users, this is ideal. The application has contextual awareness of the user (physical location; item they are holding, etc.) and there is an “awareness” of the “scene” that is likely to be played out between the User and the application. This means that the AI characters do not need to be “generalists” or be able to carry on random conversations or answer obscure questions — they need to “motivate” the User to get through the story/engagement.
This can be as simple as providing “item location” data plus providing a relevant mCoupon, or as complex as delivering transmedia story elements from a motion picture to the mobile engagement.
