No intelligence tuning. No model training. A temporal governance layer that controls behavior over time.
Modern AI systems are fast and powerful, yet they lack a fundamental capability: consistent behavior over time. Current evaluation metrics measure performance at a single moment, but they fail to detect gradual drift, instability, or silent behavioral collapse.
Core Governance introduces a non-intrusive layer that sits above any AI model. It does not alter intelligence, architecture, or training data. Instead, it observes behavior longitudinally, enforcing temporal consistency and detecting deviations before failure occurs.
Core Governance continuously observes model behavior across time. It samples outputs, decisions, and response patterns within rolling temporal windows, constructing stability signatures that represent normal behavioral continuity.
Rather than optimizing performance, the system detects divergence, drift, or instability by measuring deviation from these temporal baselines. When deviation crosses a defined threshold, risk is flagged before observable failure occurs.
No training. No tuning. No architectural interference. Only longitudinal behavioral control.
A governance core. A behavioral stabilizer. A temporal control system for AI.
Core Governance produces temporal risk signals — not predictions — indicating when a system is approaching behavioral instability over time.
Not a model. Not a framework. Not an optimization layer.