A conceptual view of the authorization path and the research extensions that could connect evidence, bounded decisions and continuous feedback.
02 / System architectureConceptual flow
Implemented baseline capabilitiesPlanned research
Request ↓
IdentityRoles & attributes
ContextRequest evidence
BehaviorPlanned research
Operational StatePlanned research
↓
Policy EngineDeterministic policy
→
Risk IntelligenceDeterministic contextual risk
→
Decision EngineAdaptive extension · planned
Behavioral intelligence + policy-bounded AI Planned research
↓
ALLOWSTEP-UPLIMITDENY
↓
TelemetryResearch instrumentation · planned
→
FeedbackContinuous loop · planned research
↳ Proposed feedback to risk assessment and policy-bounded adaptation
Conceptual research architecture, not a deployment schematic. Solid nodes represent capabilities of Models A–C; dashed nodes describe planned extensions. The output vocabulary does not assert that every model implements every action.01
Deterministic Policy
Role-based authorization and attribute conditions provide explicit rules in the implemented baselines. They form the foundation for investigating policy-bounded adaptation.
Implemented02
Contextual Risk
Model C uses deterministic contextual risk. This rule-based capability is distinct from learned behavioral anomaly detection.
Implemented03
Behavioral Intelligence
Planned investigation of behavioral evidence to help assess abnormal or potentially compromised access. No learned behavioral model is represented as implemented.
Planned Research04
Policy-Bounded AI
Proposed AI-derived evidence would operate within deterministic policy constraints. The allowed actions, explanations and handling of policy/AI disagreement require research specification and evaluation.
Planned Research05
Continuous Feedback
A proposed feedback loop would connect telemetry and observed outcomes to subsequent risk assessment. Its stability, usefulness and operational costs remain open research questions.