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The healthcare industry is undergoing a transformative shift as artificial intelligence moves from isolated predictive models to autonomous, goal-driven agents capable of reasoning, planning, and adapting in real time.
Agentic AI for Healthcare: Building Scalable Models for Production is the first comprehensive technical guide that focuses specifically on designing and deploying agentic AI systems within complex clinical and operational healthcare environments. Unlike traditional AI systems that passively infer outcomes, agentic AI involves systems that actively make decisions, coordinate with other agents, and take initiative toward long-term goals, making them ideal for dynamic and high-stakes healthcare settings. What sets this book apart is its deep technical focus tailored for computer scientists, architects, and AI engineers who are building real-world healthcare solutions. Each chapter bridges theoretical foundations with production-ready implementations using cloud-native technologies, distributed architectures, knowledge representation models, and secure deployment pipelines. With detailed case studies in oncology, vaccine management, and hospital operations, the book demonstrates how agentic AI can improve care delivery, reduce cognitive burden on clinicians, and automate routine workflows-all while meeting regulatory standards.
As healthcare increasingly adopts AI-first strategies, this book fills a critical need by offering a structured, engineering-centered approach to building scalable, intelligent, and trustworthy healthcare systems.
List of contents
About the Author. Preface. Introduction.
Chapter 1: Introduction to Agentic AI in Healthcare.
Chapter 2: Core Principles and Mechanisms of Agentic AI.
Chapter 3: Architectures for Healthcare AI Agents.
Chapter 4: Developing Scalable Agentic AI Models for Healthcare Production.
Chapter 5: Key Agentic AI Frameworks for Healthcare.
Chapter 6: Applications of Agentic AI in Clinical Settings.
Chapter 7: Agentic AI for Streamlining Healthcare Operations.
Chapter 8: Ethical and Regulatory Considerations for Agentic AI in Healthcare.
Chapter 9: The Future of Agentic AI in Healthcare.
Chapter 10: Tools and Platforms for Developing Agentic AI in Healthcare.
About the author
Sairohith Thummarakoti is a technology leader who builds agentic AI systems that work in the real world. For more than a decade, he has delivered large-scale solutions across healthcare, health insurance, banking, finance, and fintech, using Pega Cloud to orchestrate planners, trusted tools, memory with provenance, and rigorous supervision. His focus is practical: designing cloud-native architectures, streamlining enterprise workflows, and embedding intelligence into mission-critical systems while maintaining security, performance, and cost efficiency. In the Pega ecosystem, he's a Featured Member (top 52 among 764,000+ members) and a Top Contributor with over 500 accepted solutions spanning AI integration, decisioning, advanced design patterns, high availability, Pega Cloud 3 migrations, and secure API integrations.
