Model decision logic.
AI-augmented and graphically

Create and change business rules with an AI agent or graphically via drag-and-drop. The result is a readable model in the platform that your team signs off.

• Create rule types such as flow rules and decision tables— graphically yourself or with an AI agent.
• Reuse existing rules, data structures and services from other models, including versioned projects from different teams.
• Manage and navigate large rule bases with many models and packages with ease — through search, wizards, hyperlinks and dependency charts.
• Export full model documentation including the data model and rules, also for models created by an AI agent.

More on Agentic AI in Decision Management

Test and validate your business rules at any time, even without a full application or a separate test environment. New: an AI agent creates test scenarios for you, or your business experts model them themselves. Approval and accountability stay with you.

• Test-driven quality assurance with integrated model validation: an AI agent creates test cases including expected results, or you define them yourself.
• The test results clearly flag any deviation from the expected reference values.
• Test-execution statistics and highlighted execution paths show every rule in detail. An AI agent evaluates them and adds tests for paths that are not yet covered.
• Graphical step-by-step execution shows the underlying data alongside each rule, so every test run stays transparent for your experts.

More on Agentic AI in Decision Management

Now analyze and optimize the quality of your decisions with new depth. An AI agent works through your entire rule model, uncovers weaknesses and proposes improvements. Your experts also have graphical tools at hand, such as dependency charts and data usage matrices, and they can test rule models against defined simulation scenarios. That keeps every analysis visible and easy to follow.

• Dependency charts make the structure of your rule model transparent. Beyond that, an AI agent can analyze the structure and find redundant rules, conflicts and unreachable branches.
• Data usage matrices show which data your rules rely on. An AI agent identifies which inputs don’t affect a decision and suggests simplifications.
• Model simulation scenarios such as Monte Carlo or Champion/Challenger flexibly through business rules. An AI agent sets them up, runs them and recommends the best parameter set.
• Whatever goes into the model is owned by your business experts.

More on Agentic AI in Decision Management