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Client Background
The client is a major health insurer based in Pennsylvania.
Client Need
Auto-adjudication in HealthEdge leaving a subset of claims in a pended state requiring manual investigation
Operations teams spending significant effort identifying root causes and resolving pend issues
High levels of repetitive rework delaying adjudication and provider payments
Lack of automated analysis making it difficult to detect patterns and prevent recurring pend scenarios
Need for Gen AI to automatically detect, analyze, and resolve pend codes to reduce manual intervention
Solution
AI-Driven Claim Analysis: Analyzed claim-level attributes using Gen AI to uncover patterns and pinpoint the data elements correlated with pend outcomes
Prompt-Based Root Cause Detection: Designed prompts grounded in historical pend cases to automatically surface likely root causes and recommended corrective actions
Custom Claim Agents Built on Google ADK: Developed specialized AI agents using Google ADK, integrated with BigQuery and enterprise data sources to fetch relevant context and generate guided analysis
Operational Deployment on Google Agentspace: Published and orchestrated these agents within Google Agentspace, enabling operations teams to trigger pend analysis seamlessly within their existing workflows
Realized Benefits
20–30% reduction in overall pended claims
25–35% reduction in rework and resubmission cycles
Faster detection and correction of issues, improving adjudication speed and provider payment timelines
Explainable, auditable AI outputs ensuring compliance and regulatory readiness
By deploying Gen AI–powered claim analysis and custom AI agents, the client transformed a traditionally manual and time-intensive pend resolution process into an automated, guided workflow.
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