AI Observability: Monitoring & Explainability: Seeing, Understanding, and Trusting Intelligent Systems in Production

By Mohan Rayithi

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 decay

Monitor predictions, confidence, and real user impact

Explain AI decisions clearly to users, auditors, and regulators

Design end-to-end AI observability architectures

Handle AI incidents, audits, and governance with evidence-not excuses

Apply observability to GenAI and foundation models

Written 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.

• Format: Paperback
• Language: English
• ISBN: B0GPPNZYNV
• ISBN13: 9798249368203
• Release Date: February 2026
• Publisher: Independently Published
• Length: 236 Pages
• Weight: 1.23 lbs.
• Dimensions: 0.5" x 8.5" x 11.0"