Rule Decision System Integration
What this is
The design and integration of an explicit decision layer around AI systems.
This layer governs how AI behaviour is evaluated, constrained or adapted in production.
Control can be placed before execution, after execution or at multiple points in a flow, depending on system requirements. Some patterns evaluate rules before a model is called to gate or route requests and enforce strict control. Others apply rules after generation to validate or constrain outputs. More complex systems combine both, balancing determinism, flexibility, latency and risk. The right pattern depends on how tightly behaviour must be governed in production.
Decision logic is separated from application code
Rules, policies and classifiers are managed independently
Behaviour can change without redeploying models or services
Ownership and auditability are explicit
This approach can be vendor independent and is model agnostic.
When this is needed
AI is already in production
Behaviour changes cause unexpected outcomes
Multiple teams influence AI behaviour
Compliance or trust requirements exist
This work turns AI behaviour from an implicit side effect into a governed system.