1. A non-transitory computer readable medium storing a program which, when executed by at least one processing unit of a computing device, provides search engine results, said program comprising sets of instructions for: ingesting information from a plurality of data sources; creating a plurality of information objects based on the ingested information; identifying a view for the plurality of information objects, wherein the view comprises a type of functionality of data information related to the plurality of information objects; defining a state for the plurality of information objects; organizing the plurality of information objects into a pod based on the view and the state for the plurality of information objects; enriching the plurality of information objects by a knowledge expert comprising at least one of a human operator, an automated process, and a conditional process, wherein the plurality of information objects are enriched with rankings, ratings, context, comments, and categorization of variables in the information objects to provide decision criteria to an artificial intelligence search engine comprising an AI knowledge engine to define rules for weighting based on contributor status and a data enrichment system that holds definitions of sets in terms of states, views, and digital objects; creating a plurality of wise objects from the enriched plurality of information objects; organizing a plurality of nodes representing a plurality of digital wise objects into an object-oriented tree, wherein the plurality of nodes comprises a root node and a plurality of child nodes, wherein each child node is one of connected to the root node directly and connected to the root node indirectly; arranging each node a discrete distance from each other node with a weight matrix defined by a domain expert, wherein the distance between nodes is based on the weighting of variables as defined in the weight matrix; comparing a menu of different types of searches for a human user to make a selection of a particular search type, wherein a minimal path length of the distances from the root node to another node in the object-oriented tree is determined when the human user selects the particular search type, wherein the minimal path length is based on the context of the search and the relationship to the variable weightings of the objects; and providing both the menu of the different types of searches and the selection to the domain expert who revises the weight matrix based on the selection of the particular search type.