Building a secure, GenAI-ready data foundation on AWS for smarter healthcare - Impetus

Building a secure, GenAI-ready data foundation on AWS for smarter healthcare

Impetus LeapLogic™ automated a health insurer’s migration to AWS, reducing TCO, accelerating timelines, and creating a secure foundation for GenAI adoption

Business needs

A leading U.S.-based health insurer, serving millions through Medicaid, Medicare and prescription drug coverage, faced mounting pressure to modernize its data and analytics ecosystem.

  • Aging legacy technology stack slowed operations, limited scalability, and hindered timely insights
  • Increasing regulatory and compliance pressures like HIPAA, CMS, and state mandates required stronger governance, auditability, and secure access to sensitive health data
  • Provider tax litigations, rising labor and medical costs, and shrinking Medicaid enrollment were thinning operating margins to <1%
  • Expensive Teradata licensing, siloed ETL tools, and complex orchestration flows increased TCO while dragging down agility
  • Long, manual development cycles and lack of elasticity prevented real-time analytics and restricted GenAI readiness

Strategic goals

To remain competitive and improve member services, the insurer wanted to:

  • Modernize its data estate – warehouse, ETL, and orchestration – to reduce cost and complexity
  • Accelerate insights across claims, fraud detection, and member analytics
  • Strengthen compliance and security with a cloud-first, HIPAA/HITRUST-compliant data foundation
  • Prepare for the future by enabling safe and scalable GenAI adoption

Solution

The insurer partnered with Impetus and AWS to modernize its data estate through LeapLogic-powered automated migration and re-engineering.

Solution highlights

  • End-to-end comprehensive assessments of data warehouse, ETL, orchestration, and consumption layers to identify high-impact migration opportunities
  • Automated conversion of Teradata workloads and ETL pipelines into Amazon Redshift and AWS Glue, cutting risk and manual effort of manual re-engineering
  • Complex StoneBranch jobs and custom scripts were consolidated into Amazon MWAA (Airflow), enabling scalable, resilient, and simplified workflow management
  • Talend workloads were rebuilt natively in AWS Glue while preserving business logic, ensuring business continuity and faster adoption.
CategoryLegacy stackModernized on AWSImpact
Data warehouseTeradata VantageAmazon RedshiftElastic scaling, lower TCO, faster query performance
ETL / integrationTalend, Informatica, WhereScape, Stored ProceduresAWS GlueServerless automation, reduced manual coding, preserved business logic
Orchestration / schedulingStoneBranch, custom scriptsAmazon MWAA (Airflow)Unified workflows, simplified orchestration, higher reliability
Analytics & statistical processingSASAWS-native analytics stack (Glue + Redshift + ML/AI services)Real-time analytics, advanced AI/ML readiness
Reporting / BISSRS (SQL Server Reporting Services)Amazon QuickSight & Redshift integrationsModern BI dashboards, real-time insights, better user experience
Governance & complianceFragmented, manual controlsHIPAA/HITRUST-ready AWS-native architectureStronger data security, auditability, regulatory compliance

What was once a fragmented, manual, and costly legacy stack became a secure, automated, AWS-native platform, unlocking agility, compliance, and the ability to confidently scale GenAI in healthcare services.

Impact

The automated platform modernization delivered measurable improvements across speed, cost, efficiency, and innovation:

  • Faster modernization at scale: Multiple Teradata and ETL workloads were migrated within months, accelerating time-to-value
  • Cost efficiency & TCO reduction: Eliminated expensive Teradata and legacy ETL licenses, moving to AWS-native Redshift and Glue for significant infrastructure and licensing costs savings
  • Automation-driven benefits: LeapLogic automated schema, code, and workflow conversions, reducing manual re-engineering time, effort, and risk
  • Enhanced operational agility: Streamlined, AWS-native orchestration flows improved the reliability and timeliness of claims and reporting processes
  • Future-ready platform: The new foundation supports both batch and real-time analytics, positioning the insurer to safely advance GenAI for claims optimization, member services, and fraud prevention

Choose a lab aligned to your Data & AI journey

Address your desired use case across critical analytic dimensions

  • Collaborate with experts on strategic objectives

  • Identify and select core technologies

  • Ensure IP governance and protection

  • Align business outcomes with goals


  • Explore architecture options with experts

  • Ensure alignment of business and technology
  • Architect an ideal solution for a pressing problem


  • Validate or refactor existing architecture
  • Develop a prototype with expert guidance

  • Establish a roadmap to production


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