ERS combines several disciplines to deliver the type of business policy automation we call rule-based systems. The first is a clear understanding of the tools and techniques of decision theory that allo us to capture and organize the data, rules, constraints and preferences of your business. The second is knowledge of programming languages and the appropriateness of different languages for solving different types of problems. Finally, we employ a deep understanding of rule-based systems: what they are, what they require to work well, and when and how to apply them.

Rule-based systems are themselves a 'best practice' in the business of automating business policy. A rule-based system always includes a rule execution component and often a rule repository as well. A rule repository is a data base of rules, the 'if-then' constructs that run your business process, that can be controlled, accessed, populated, exported and analyzed as with any data base. A rule or inference engine is the rule execution component that invokes the right rules given the data that is present. A rule engine consists of a rule base (those rules from the repository), a rule matching component, an agenda of rules that can be executed, and working memory where data about the problem being solved resides. As rules are executed, working memory changes and the agenda for rule execution changes.

ERS has an exceptional track record for applying rule-based systems to solve hard business problems. Let us show you how we can put this technology to work for you!