OpenRules allows business users (subject matter experts with no programming experience) to create, test, and maintain operational decision models. The best way to learn how to create your own decision models is to analyze existing examples. You can start with simple decision models described in detail below:
- Hello: defines how to greet a customer based on the time of day, gender, and marital status
- PatientTherapy: specifies decision logic for helping a doctor to determine a patient’s therapy
- UpSellRules: demonstrates how to deal with arrays of objects using relatively complex up-sell rules
- Vacation Days: determines the number of vacation days assigned to an employee based on age and years of service
- Iterations: demonstrates how to iterate over an array of employees to determine the minimum or maximum salaries, the total number of children, all locations where the employees live, and similar requests.
After OpenRules installation (evaluation or commercial), you will find many examples of decision models in the folder “openrules.samples“. These decision models are distributed between the following sub-folders devoted to different decision modeling capabilities:
INTRO: simple introductory decision models, such as those described above.
ITERATIONS: decision models that deal with arrays/lists of objects and various iterations over them.
MATCHING: decision models with complex matching conditions and regular expressions. Read more.
CSV: decision models accessing data from large CSV files. Read more here and here.
DEPLOYMENT: demonstrate different deployment and integration options for the same decision model, “Vacation Days“.
DB: decision models that demonstrate the use of Rule DB™, an OpenRules component that supports connectivity with relational databases. Read more: RuleDb samples, SoldierPayments, Big Decision Tables
ARCHITECTURE: decision models that demonstrate how to build Enterprise-Level Rules Repositories. See a more complex sample “Loan Services“.
AI: decision models deployed as AI Agents using MCP Servers and running from LLMs
LOAN: decision models related to loan origination.
SORT: decision models that demonstrate how to sort collections of objects. See also
TEMPLATES: domain-specific decision table templates
ADVANCED: more complex decision models, such as:
- 1040EZ: tax calculation
- FlightRebooking: reschedules passengers from a canceled flight
- InsurancePremium: calculates the insurance premium for an automobile policy
- OrderPromotion: defines promotions for different sales orders
- SelectingUniversityDegrees: describes a decision service that allows a student to select all necessary university courses to receive a desired degree.
MISC: miscellaneous decision models.
Sample decision models for RuleSolver and RuleLearner have been included in their standard installations.
You can use these and many other provided decision models to create your own models by adding your own decision variables and business rules. OpenRules also provides a User Manual for Business that doesn’t require any preliminary knowledge.
Decision Intelligence Platform 