Oak is formal logic based optimization and prediction. Optimization is based on accurate modelling of underlying uncertainty and non-determinism, and prediction is logical entailment rather than simple computational feedforward.

Risk management then controls and represents many-valuedness of underlying data, and, moreover, builds upon an establishment of formal logic based guidelines for business decisions. The success of business then lies, not only in smart analysis of data, but in ontology based representation of it as prerequisite for groundbreaking knowledge representation of business actions.

The key is being sound and appropriately logical about vagueness, in fact controlling it and not be controlled by it.

Traditional optimization and predicton are contradictory in their assumptions that underlying information are accurate. Modelling over these data are always incomplete and inaccurate. Modelling risk and chance should not allow for uncontrolled uncertainty.