Contact Me
Contact Me

Transform Your Healthcare Payer Organization with Agentic

About The Book
Buy The Book

Watch Book Trailer

Chapters Inside The book

Chapter 01
Chapter 01
This chapter introduces Agentic AI as a new way of thinking about intelligent systems. Instead of static models that only predict outcomes, Agentic AI uses autonomous agents that can perceive their environment, reason through goals, and act in real time. The chapter explains how these agents communicate, negotiate, and self-organize to deliver results. Readers learn why this model is more suitable for complex healthcare payor operations compared to traditional approaches. Real examples show how claims processing, fraud detection, and member engagement become faster and more accurate. The chapter also highlights possible risks and shares practical methods to manage them without slowing innovation.
Buy Now
Chapter 02
Chapter 02
This chapter presents a clear view of what healthcare payors do and how their organizations function. It explores their core business processes, including eligibility checks, claims handling, provider payments, and regulatory compliance. The author explains how economic pressure, changing policies, and rising service expectations impact every decision payors make. Data flows from members, providers, and internal systems are examined so readers can see why bottlenecks occur. A case scenario from a real working day helps illustrate the challenges and inefficiencies that employees and systems face inside a payor organization.
Read More
Chapter 03
Chapter 03
The third chapter reveals the problems that hold payors back from operating at their full potential. Operational delays, billing errors, regulatory burdens, inconsistent data, and manual interventions create massive strain on teams and budgets. The author shows why older systems and isolated digital tools have failed to solve these problems even after years of investment. Human fatigue, outdated processes, risk exposure, and slow decision cycles leave organizations vulnerable and inefficient. A structured risk matrix helps readers understand which issues demand immediate attention. By the end of the chapter it becomes clear that an intelligent and adaptive solution is needed to drive real transformation.
Read More
Chapter 04
Chapter 04
This chapter guides readers through the architectural design of an Agentic AI system built specifically for healthcare payors. The system is organized into layers that manage governance, perception, reasoning, and action so agents can make decisions with clarity and accountability. Each layer supports scalability, data security, and compliance without sacrificing performance. A claim adjudication example walks the reader through how agents evaluate information, make decisions, and collaborate to complete a case. The chapter also explains how cross layer observability ensures transparency and trust inside the organization.
Read More
Chapter 05
Chapter 05
The knowledge graph described in this chapter forms the foundation of the entire agentic ecosystem. It defines how entities, relationships, contracts, treatment codes, and business rules connect and interact in real time. Readers learn how to structure an ontology that supports healthcare processes, how to ingest data, and how to maintain explainable query responses. Provenance tracking, access control, and governance practices are explained in practical terms so the system remains secure and compliant. The chapter concludes with a realistic 12-month roadmap that shows how organizations can implement a knowledge graph step by step.
Read More

Chapters Inside The book

Chapter 01

This chapter introduces Agentic AI as a new way of thinking about intelligent systems. Instead of static models that only predict outcomes, Agentic AI uses autonomous agents that can perceive their environment, reason through goals, and act in real time. The chapter explains how these agents communicate, negotiate, and self-organize to deliver results. Readers learn why this model is more suitable for complex healthcare payor operations compared to traditional approaches. Real examples show how claims processing, fraud detection, and member engagement become faster and more accurate. The chapter also highlights possible risks and shares practical methods to manage them without slowing innovation.
Buy Now

Chapter 02

This chapter presents a clear view of what healthcare payors do and how their organizations function. It explores their core business processes, including eligibility checks, claims handling, provider payments, and regulatory compliance. The author explains how economic pressure, changing policies, and rising service expectations impact every decision payors make. Data flows from members, providers, and internal systems are examined so readers can see why bottlenecks occur. A case scenario from a real working day helps illustrate the challenges and inefficiencies that employees and systems face inside a payor organization.
Buy Now

Chapter 03

The third chapter reveals the problems that hold payors back from operating at their full potential. Operational delays, billing errors, regulatory burdens, inconsistent data, and manual interventions create massive strain on teams and budgets. The author shows why older systems and isolated digital tools have failed to solve these problems even after years of investment. Human fatigue, outdated processes, risk exposure, and slow decision cycles leave organizations vulnerable and inefficient. A structured risk matrix helps readers understand which issues demand immediate attention. By the end of the chapter it becomes clear that an intelligent and adaptive solution is needed to drive real transformation.
Buy Now

Chapter 04

This chapter guides readers through the architectural design of an Agentic AI system built specifically for healthcare payors. The system is organized into layers that manage governance, perception, reasoning, and action so agents can make decisions with clarity and accountability. Each layer supports scalability, data security, and compliance without sacrificing performance. A claim adjudication example walks the reader through how agents evaluate information, make decisions, and collaborate to complete a case. The chapter also explains how cross layer observability ensures transparency and trust inside the organization.
Buy Now

Chapter 05

The knowledge graph described in this chapter forms the foundation of the entire agentic ecosystem. It defines how entities, relationships, contracts, treatment codes, and business rules connect and interact in real time. Readers learn how to structure an ontology that supports healthcare processes, how to ingest data, and how to maintain explainable query responses. Provenance tracking, access control, and governance practices are explained in practical terms so the system remains secure and compliant. The chapter concludes with a realistic 12-month roadmap that shows how organizations can implement a knowledge graph step by step.
Buy Now

Ripunjaya

Pattnaik

He is a Senior Solutions Architect at Amazon Web Services with nearly two decades of experience guiding organizations through cloud transformation. His career spans industries that demand precision and trust, including healthcare, life sciences, finance, and media. From large scale data platforms to secure AI architectures, he has led solutions that deliver real business outcomes. His work has supported Fortune 500 and Fortune 100 companies in solving complex technical and operational challenges.

Known for his deep expertise in Agentic AI, he regularly conducts workshops that translate advanced concepts into clear, actionable strategies. His mindset is grounded in practical implementation, focusing on tasks such as modernizing claims processing, improving fraud detection, and building strong compliance frameworks. Every design decision reflects a balance of technology, ethics, and measurable value. It was this hands-on perspective, consistently praised by colleagues and customers, that inspired him to write his first book.

Read More

AGENTIC AI FOR
Healthcare PAYORS

TRANSFORMING CLAIMS, FRAUD, AND MEMBER EXPERIENCE

This book takes readers inside a new era of intelligent healthcare systems, showing how Agentic AI can reimagine the core functions of payor organizations. Instead of relying on static automation, agent-based models think, act, and adapt in real time. Claims adjudication, compliance checks, and operational workflows become smarter, faster, and more resilient. The goal is to help payors move beyond manual processes and embrace scalable, high trust decision making.

Its impact reaches far beyond the technical layer, touching member experience, provider relationships, and financial stability. Agentic AI enhances fraud detection, reduces administrative burden, and brings consistency to complex policies. Practical scenarios, architectural models, and real deployment insights give both executives and engineers a clear path to implementation. In every chapter, the book demonstrates how healthcare payors can transform not just their systems, but the quality of service they deliver.

Buy Now
Read More

Book Trailer

Clients testimonials

The book helped our leadership understand why traditional automation fails and how autonomous systems can drive real value. It is visionary and pragmatic at the same time

Christopher Lane

This is the first time I have seen claims adjudication explained with such depth and practicality. Every payor team should read this.

Natalie Singh

Agentic AI for Healthcare Payors opened my eyes to how automation can be truly intelligent. This is not another technology book. It is a strategic blueprint for the future.

Priya Menon

This book explains complex ideas in a way that every leader can understand. It is practical, grounded, and deeply relevant to our industry.

Jonathan Reese

As someone working in claims operations, the architecture and case studies felt like a mirror to our daily challenges. This book offers solutions we can actually use.

Michael Donovan

Ripunjaya shows what is possible when innovation meets experience. I found the real world examples incredibly valuable.

Dr. Sara Kim

Agentic AI is the next leap in healthcare technology and this book gives clarity on how to approach it, scale it, and govern it.

Emily Harrison

What impressed me most was the honesty in explaining risk, compliance, and data responsibility. It does not promise magic, it delivers guidance.”

Carlos Ramirez

As an AI engineer, the agent architecture and ontology framework were exceptional. Finally a healthcare book that does not hide the technical details.

David Chen

I rarely recommend books to my executive peers, but this one is different. It speaks to the pain, the responsibility, and the opportunity that payors face today

Linda A. Foster

blogs we have

Discover short, insightful articles that simplify healthcare technology and share practical ideas for modern payor challenges.

Blogs

Nov 26, 2025

The Future of Healthcare Payors and How Agentic AI is the Next Big Shift

Healthcare payor organizations are under constant pressure. Every day, they process claims, respond to providers, address member concerns, and navigate a maze of compliance rules.

Read More

Nov 26, 2025

How Agentic AI is Redefining Healthcare Payor Operations

Healthcare payors operate in an environment full of complexity. They manage millions of claims, navigate regulatory changes, and handle member and provider communications daily. With so many moving parts, organizations often struggle with inefficiencies, delays, 

Read More

Nov 26, 2025

Unlocking Operational Excellence in Healthcare Payors with Agentic AI

Healthcare payor organizations face an increasingly complex landscape. Rising operational costs, evolving regulations, and the need to deliver exceptional member experiences create constant pressure.

Read More
View All