Kalyana Gajapathi Raju Konduru

Architecting Enterprise Generative AI for Automated Pricing and Contract Decisioning in PBM

Abstract:

Pharmacy Benefit Management (PBM) organizations face growing complexity in administering prescription drug benefits across health plans, employers, pharmacies, and manufacturers. Pricing and contract configuration have traditionally relied on manual, spreadsheet-driven processes involving Excel workbooks and email approvals, creating bottlenecks, inconsistency, and limited traceability as rebate complexity and regulatory requirements continue to expand.
This session presents an enterprise architecture that integrates deterministic business rules with generative AI to improve decision quality while preserving governance and compliance. The approach combines Spring AI for orchestration, LangChain4j for prompt workflows, large language models for reasoning, and Retrieval-Augmented Generation (RAG) to ground pricing decisions in authoritative contracts and policies. A decisioning pipeline ingests contracts, extracts clauses, validates business rules, and produces explainable, auditable outputs, allowing human reviewers to focus on exceptions rather than routine processing.
The discussion also addresses enterprise deployment through microservices, Kubernetes and OpenShift, and the security and HIPAA considerations essential to protecting sensitive healthcare data, including encryption, access control, and audit trails. Attendees will gain a practical framework for building explainable, compliant AI systems, along with insight into how autonomous agents and continuous policy learning will shape the future of enterprise pricing decisioning in healthcare.

Profile:

Kalyana Gajapathi Raju Konduru is an AI Full Stack Technical Leader and Senior Software Engineering Advisor with 18+ years spent building mission-critical systems for healthcare, insurance, and financial services organizations. He specializes in turning legacy monoliths into resilient microservices ecosystems and, more recently, embedding generative AI, from Retrieval-Augmented Generation (RAG) pipelines to autonomous AI agents, directly into enterprise engineering workflows.
At Evernorth (Cigna), Kalyan leads the architecture behind pharmaceutical rebate and pricing platforms that process millions of transactions a day, work that has delivered over $200 million in documented business value. He's equally known for championing AI-assisted development across engineering teams, driving early, practical adoption of tools like GitHub Copilot and Cursor long before they became industry standard.
Kalyan brings a rare combination to the stage: deep hands-on architecture experience (React, Spring Boot, Kafka, Oracle, MongoDB) paired with real-world lessons on scaling AI adoption inside large, risk-averse enterprises. His talks translate high-stakes, regulated-industry engineering into practical takeaways for teams navigating their own AI and microservices transformations.
An AWS Certified Solutions Architect and Cigna GenAI Technologist, Kalyan has led teams of up to 25 engineers through zero-downtime migrations and multi-million-dollar modernization efforts, and enjoys unpacking what actually works (and what doesn't) when rolling out AI at enterprise scale.