AI-Agents Driven Claims Workflow Automation

This project introduces an Agentic AI‑powered claims workflow solution designed to transform healthcare revenue cycle management. One of the most persistent challenges in the industry is claim denials and rejections, often caused by errors in patient information, coding mistakes, or insufficient documentation. These denials slow down reimbursement, create cash flow issues, and increase administrative burden. Leveraging agentic AI, the solution deploys autonomous agents that seamlessly handle training, inference, and routing of claims data. A Training Agent builds machine learning models from historical claims, while an Inference Agent applies those models to new encounters, predicting outcomes before submission. Data pipelines ensure inputs and outputs flow seamlessly between agents, IBM Cloud Object Storage, and Watsonx Orchestrate workflows. The result is faster claims processing, reduced manual workload, improved accuracy, and secure, reproducible integration with existing systems. This project demonstrates how agentic AI can move healthcare organizations from reactive claims management to proactive, intelligent automation — ultimately accelerating reimbursements and improving operational efficiency.