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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The Problem

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Without clear visibility into these changes, mission systems risk operating on outdated or unreliable intelligence.

The Solution

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.