Drift Identification & Assessments with Graphics (DIAG)
Understand What’s Changing. Maintain What Matters.
DeNOVO-DIAG is an advanced model monitoring and analysis capability designed to detect and assess drift in AI/ML systems operating across dynamic mission environments. As data, signals, and operational conditions evolve, DIAG provides real-time visibility into how models are performing, what is changing, and why it matters.
Built for defense and intelligence applications, DIAG transforms complex model behavior into clear, visual insights enabling rapid understanding, informed decisions, and sustained mission accuracy.
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AI/ML models deployed in real-world environments degrade over time.
Changes in signal patterns, data distributions, and operational context can introduce:Reduced model accuracy and confidence
Hidden bias or misclassification risks
Delayed detection of performance degradation
Increased analyst workload to validate outputs
Without clear visibility into these changes, mission systems risk operating on outdated or unreliable intelligence.
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DeNOVO-DIAG provides a structured, transparent approach to model drift detection and analysis:
Drift Identification – Detects shifts in input data, feature distributions, and model outputs
Performance Assessment – Quantifies impact to accuracy, precision, and mission effectiveness
Visual Analytics – Delivers intuitive graphics that clearly show what is drifting and where
Actionable Insights – Enables rapid decisions on retraining, tuning, or model replacement
DIAG ensures that AI/ML systems remain aligned with mission reality—continuously.