Human-in-the-loop claims processing with Amazon Bedrock AgentCore

This article presents a human-in-the-loop framework for claims processing using Amazon Bedrock AgentCore, enabling incremental autonomy progression from assisted drafting to supervised autonomy to selective full autonomy.

• Autonomy progression model: Assist mode (agent drafts, human approves), Supervised autonomy (agent handles routine cases, humans review exceptions), Full autonomy (agent decides on proven case types)
• Cedar policies define authorization boundaries declaratively, specifying what agents can and cannot do per program and case type
• Amazon Bedrock AgentCore components: Knowledge Bases for policy retrieval, Memory for case context, Runtime for isolated reasoning, Gateway for external system access
• Three HITL mechanisms: Cedar policies as approval gates, AWS Step Functions for workflow checkpoints, AWS Lambda interceptors for dynamic escalation
• Addresses state eligibility challenges: SNAP error rates must stay below 6%, caseworker turnover exceeds 30%, caseloads outpace hiring

The framework enables caseworkers to focus on complex cases while agents handle routine determinations, maintaining error rates within federal tolerance while reducing backlogs.