Enterprise AI in the Cloud 1st Edition

Capture the competitive edge of cloud-native intelligence with Enterprise AI in the Cloud (1st Edition) by Rabi Jay. This concise, practical guide cuts through hype to show how organizations can design, deploy, and scale AI across AWS, Azure, GCP, hybrid and edge environments.

Inside you’ll find clear, real-world guidance on architecture patterns, MLOps pipelines, model governance, security and compliance, cost optimization, and cloud-native tooling. Rabi Jay combines hands-on deployment blueprints with strategic frameworks so technical leaders and cross-functional teams can translate AI pilots into production-grade, measurable business impact.

For CTOs, data scientists, ML engineers and product managers, this book delivers actionable checklists, decision trees and case examples from enterprises in North America, Europe and Asia-Pacific—making it relevant for global teams navigating regional compliance and operational constraints. Learn how to choose the right cloud strategy, avoid common migration pitfalls, and implement reliable monitoring, retraining and continuous delivery for models.

Readable yet authoritative, Enterprise AI in the Cloud blends technical depth with business-minded outcomes: faster time-to-value, reduced risk, and scalable AI services that align with corporate governance. If you’re leading AI transformation or accountable for cloud strategy, this book is a practical roadmap.

Order your copy of Enterprise AI in the Cloud (1st Edition) by Rabi Jay today to move from experiments to enterprise-grade AI in the cloud.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.