One of the core aspects of Rulevolution is the ability to manipulate data by the creation of behaviour (sometimes referred to as rules). Each item of behaviour (rule) is created against an incoming, which then has a result and a reason
The reason differentiates Rulevolution to other data processing engines (note that we don't consider Rulevolution to be a rules engine in the traditional sense, as it is capable of much more).
At every point that a user attempts to create a new element of behaviour, all existing reasons (Note: not results) are compared, allowing the engine to spot conflicts of logic. This safeguard ensures that the ruleset created internally is consistent, and therefore the system as a whole does not have unexpected behaviour (a common problem with existing rules engines).
Rulevolution uses a layer of Machine Learning to ensure consistency within the system.