01
Author
Analysts write rules as decision tables in MS Excel or Google Sheets, with built-in LLM assistance. No proprietary language, no separate authoring tool.
Decision intelligence, made executable
Build decision services that find the best answer.
- Model the decision.
- Find the best outcome.
- Deploy it everywhere.
- Connect it to AI.
- Understand why it decided.
20+years in production
Business-firstdecision modeling
Deploycloud or on-premises
AI Integrationplain English interaction
Sample Decision Model
LOAN SELECTIONFinding Optimal Decision
Customer factsIncome + debt
Term range24–96 months
StepDecision tableAction
01Define loan amount, term, and paymentVary
02Apply the loan eligibility constraintFilter
03Maximize the integrated objectiveSolve
DecisionBest eligible output combination
Alternatives evaluatedThomson ReutersAdobeBayerMerckJ.P. MorganRoyal Bank of ScotlandCommerzbankLockheed MartinNorthrop GrummanNTT DATASaint-GobainSwissportInternal Revenue ServiceUNITEDFiservLonPacAXAState Street
How it works
One decision model, from first rule to production service.
Every capability in the platform attaches to the same model. There is no proprietary rule language and no separate authoring tool to learn. Business experts define what the decision must accomplish. Developers decide how it connects and runs.
02
Model, test, debug
The Decision Modeling IDE builds decision diagrams from the model and steps through rules one at a time. Test suites run against the same tables the business owns.
03
Deploy
Ship the same model as a decision service: REST endpoint, serverless function, container, or AI agent. Every execution is logged and explainable.
04
Extend
Learn rules from historical data, solve optimization problems, read from relational databases, and let business users compare options at decision time.
Learn by building
Start with a working decision.
01 / RULES
Rules-based Decision Models
Start with approachable rule-based services, then move into enterprise-level decision models.
02 / OPTIMIZEDecision models with Optimization
See a decision model 'Loan Selection' that evaluates eligible combinations of loan amount and term, then selects the option that best meets the objective.
03 / LEARNLearn Rules from Examples
See how machine learning can generate understandable decision rules for expert review.
A simple first decision service
Change the facts. Follow the rules.
The Vacation Days model calculates an employee’s allowance from age and years of service. It is a straightforward rules example—not an optimization model—so you can focus on transparent logic, testing, and integration.
Study the complete modelVacation allowance24 days
✓Base allowance+22
—Age/service rule+0
—Senior-service rule+0
✓Experience rule+2
Base 22 days plus 2 days for an employee with 15–29 years of service or age 45+.
Why OpenRules
More than a rule engine.
OpenRules is a Decision Intelligence Platform for engineering transparent, executable operational decisions - not just managing business rules. One decision model can combine business rules, optimization and machine learning, while the same model is debugged, tested, explained and deployed as an operational service. OpenRules Competitive Distinction
The optimal decision
Don’t stop at the first valid answer.
Most rule engines determine whether an answer is valid. OpenRules can model constraints, produce multiple feasible decisions, and optimize them against business goals.
See the Loan Selection modelFeasible loan82objective score
Best loan96objective score
Feasible loan87objective score
Business-expert authoring. Powerful optimization. Intuitive decision tables.
Minimal learning curve. Use familiar tools to create and maintain decision tables of any complexity. Express business rules, constraints, and objectives without forcing domain experts to learn a specialized rules or optimization language.
20+
Years of real-world decisioning.
OpenRules decision services have operated in multi-year production environments across complex industries.
“OpenRules has the most aggressive approaches to business-expert authoring and typically requires less developer support than IBM ODM, FICO Blaze Advisor, and Red Hat Drools.”
Performance
Superfast—even with very large decision tables.
OpenRules is engineered for high-volume operational decisions, with optimized BigTable execution for large rule sets. In a published benchmark using a 16,369-rule decision table, the Java API processed more than 100,000 requests per second.
100K+requests per second
16,369rules in the decision table
Built for decisions that matter
Transparent by design.
Reliable by experience.
OpenRules has supported production decision services for more than two decades. Every model can be tested, versioned, inspected, and explained before it becomes part of a critical application.
Bring your own decision
Turn your idea into a working Decision Service for free.
The OpenRules team will develop a Decision Service for your business problem and rules. After an online scoping session, you can test it remotely in the cloud—without installing anything.
What to bring
01
A brief project description and its main objective
02
Sample input data and the results you expect
03
Business rules in plain English, Excel, or another clear format
2–3 daysTypical delivery after the scoping meeting
Your first decision service
Make the logic visible.
Make the outcome better.
Download a fully functional evaluation of OpenRules Decision Manager and build with included sample projects.
We can help you build your decision-making services and train your team to run and maintain them without us.
Industry Awards
