Normalized claim
Call hold time: 19% decrease
decreased call hold time — the time during which a caller is on hold while the service representative researches the matter — by approximately 19 percent
New York Life Reframes Its Approach to Data and AI Using AWS
Use case typeData platform modernizationUpdated Jul 15, 2026
New York Life modernized its legacy data infrastructure on AWS to create a unified data foundation for AI and analytics. The insurer built Service Sage with Amazon Bedrock to help service representatives retrieve relevant information from policy documents and knowledge bases during customer calls.
- Organization
- New York Life
- Industry
- Insurance
- Location
- United States
- Published
- July 2026
Reported outcomes
110,000 count
questions answeredOther quantified impact
−19%call hold time
Strategic outcomes
Other strategic outcomeDecommissioned the legacy Hadoop environmentRisk & complianceStrengthened data governance and provenance trackingEmployee experienceImproved employee satisfaction and reduced attrition
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Questions answered: 110,000 count increase
In the 7 months since launch, the solution has helped agents answer around 110,000 questions
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- New York Life
- Provider
- AWS
- Maturity
- Unknown
- Linked source
- AWS Solutions Case Study
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 2 of 2
- 1Data platform modernization
- 2Customer service automation
- New York Life's on-premises Apache Hadoop data lake was approaching end of life.
- The system supported over 100 data sources and created silos across business divisions, causing inconsistent customer experiences and limiting AI potential.
- The company migrated and reimagined its data foundation on AWS using Amazon Redshift, AWS Glue, Amazon S3, Amazon Athena, Amazon Bedrock, Amazon OpenSearch Service, and Amazon DynamoDB.
- Service Sage uses Amazon Bedrock generative AI with a vector database in Amazon OpenSearch Service and Amazon DynamoDB for logging and prompt management.
- The unified platform gives teams a shared system and data layer for operations, analytics, and AI experimentation.
- The article says Service Sage reduced call hold time by approximately 19 percent.
- In seven months, it helped agents answer around 110,000 questions.
Architecture
New York Life built a modern data foundation on AWS centered on Amazon Redshift and AWS Glue, with Amazon S3 for centralized storage and Amazon Athena for analytics and AI experimentation. Service Sage uses Amazon Bedrock to retrieve answers from policy documents and knowledge bases, with Amazon OpenSearch Service providing vector search and Amazon DynamoDB used for logging and prompt management.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jul 15, 2026Publisher: AWSEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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