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Production AI Radar
Model registry + eval gates
Versioned models with promotion criteria tied to offline and online evals.
AdoptMLOps
- Why this ring
- Every production ML team we audit without a registry cannot answer which model is live, who approved it, or how to roll back.
- Production risk if ignored
- Undetected model drift and unapproved promotions reach customers before monitoring catches them.
- EU AI Act relevance
- Supports technical documentation and change traceability for high-risk AI systems.
- Typical effort
- weeks
- Medium FinOps impact
Use cases
- Enterprise asks which model is live
- Rollback takes hours
- No approval trail for promotions
Adoption steps
- Register all production candidates in MLflow
- Define Staging → Production with eval gate tags
- Wire CI to fail on metric regression
- Export registry history for compliance quarterly
Related tools
In your assessment
Registry maturity score + promotion workflow review