Mainframe to Guidewire ClaimCenter Migration Agent

Overview

Transform your legacy mainframe claims infrastructure into modern Guidewire ClaimCenter implementations with our intelligent AI migration agent. Purpose-built for insurance carriers undertaking digital transformation, this solution automates the complex process of mapping mainframe data structures to Guidewire schemas—eliminating months of manual effort and reducing mapping errors by up to 95%.

The Challenge

Traditional mainframe-to-Guidewire migrations face a critical bottleneck: scarce expertise. Business analysts and SMEs who understand both mainframe structures and Guidewire data models are increasingly rare. Most professionals have deep knowledge of only one platform, making it extremely difficult to execute complex mappings—especially one-to-one, one-to-many, and many-to-one relationships across ~1,000 mainframe attributes to 40,000+ Guidewire ClaimCenter attributes needed to capture the full depth of insurance claims processing.

The Solution

The agent leverages advanced mapping capabilities utilizing vector databases consisting of client-specific mainframe custom schemas and Guidewire ClaimCenter v9 and v10 data dictionaries. Previously, this work was performed manually by BAs and SMEs who understood both Guidewire and mainframe attributes—a skillset that is increasingly scarce. Today's BAs typically have expertise on only one platform, making complex mappings exceptionally challenging.

The GenAI agent operates on vector databases built using Amazon OpenSearch Serverless, sourced from client-specific mainframe schemas and Guidewire ClaimCenter v9/v10 data dictionaries securely hosted in Amazon S3.

Chunking optimization ensures efficient semantic retrieval, while Amazon Bedrock–based agents—reinforced with guardrails for data security, governance, and accuracy—drive intelligent multi-phase workflows that automate mapping, transformation, and validation.

The agent analyzes mainframe attributes to recommend optimal Guidewire matches (supporting one-to-one, one-to-many, and many-to-one relationships), automates data type and business logic conversions (e.g., COBOL to Guidewire configuration), and performs end-to-end validation by linking mainframe tables to corresponding Guidewire entities with lineage and sample comparisons—all within a guided, GenAI-driven environment that minimizes manual effort and ensures consistent, compliant results.