6. The method of claim 1 , further comprising storing the types in a type schema comprising both a relational data store and non-relational data store, wherein data identities and data relationships are modeled in the relational data store, extended instance properties are modeled in a non-relational data store.
1. A computer-implemented method for providing a predictive intelligence platform, comprising: receiving from a user through a meta application programming interface (API) definitions for predictive intelligence (PI) artifacts that describe a domain of an online transaction system for at least one business entity, each of the PI artifacts including types, component modules and behavior bundles; exposing a domain-specific entity API, based on the PI artifacts, for receiving entity events from the online transaction system, the entity events comprising records of interactions and transactions between customers and the online transaction system; responsive to receiving an entity event through the domain-specific entity API, executing the component modules and behavior bundles related to the entity event to analyze relationships found between past entity events and metrics associated with the past entity events to compute at least one of a probabilistic prediction and a score related to the entity event, and returning an advisory response to the online transaction system comprising the at least one of a probabilistic prediction and score so the at least one business entity can use the advisory responses to make business decisions regarding the entity events; and allowing the user to optimize the PI artifacts by saving past entity events as entity event replicas and processing the entity event replicas using modified versions of one or more of the event API, the types, component modules and the behavior bundles for experimentation.