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AI OBSERVABILITY : Monitoring & Explainability : Seeing, Understanding, and Trusting Intelligent Systems in Production by Mohan Rayithi
English | February 22, 2026 | ISBN: N/A | ASIN: B0GPN4MHN7 | 239 pages | EPUB | 1.20 Mb
AI systems don't fail loudly. They fail silently.
Models drift. Bias creeps in. Predictions look confident-until trust collapses.
Traditional monitoring can't see it. Accuracy can't explain it. And dashboards can't defend it.
AI Observability: Monitoring & Explainability is the definitive guide to building AI systems you can see, understand, govern, and trust-in production, at scale, and under scrutiny.
This book goes far beyond theory. You'll learn how to:Detect data drift, bias, and silent model decayMonitor predictions, confidence, and real user impactExplain AI decisions clearly to users, auditors, and regulatorsDesign end-to-end AI observability architecturesHandle AI incidents, audits, and governance with evidence-not excusesApply observability to GenAI and foundation modelsWritten for real-world engineers, architects, leaders, and auditors, this book transforms AI from a black box into an accountable system.
If you deploy AI in production, this book is no longer optional.
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