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
etect 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.
Links are Interchangeable - Single Extraction
