AEGIS-X Telemetry Platform
Model-Agnostic AI Reliability, Uncertainty Estimation & Early Warning System
An advanced independent engineering framework that wraps production machine learning models to detect out-of-distribution (OOD) inputs, calculate epistemic prediction uncertainty, track feature drift, and output actionable reliability diagnostics.
Architectural Constraints & Friction
Machine learning models in production silently degrade when encountering out-of-distribution edge cases or shifting real-world data patterns. Existing tools either require intrusive retraining or fail to provide unified reliability warning signals.
System Design & Implementation
Designed AEGIS-X to surround models externally without modifying weights. Implemented a multi-stage reliability pipeline: reference contract validation, OOD density scoring, epistemic uncertainty measurement, feature drift detection, and fused reliability score calculation.
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