AWS Glue

AWS Glue is a serverless data integration service that discovers, prepares and integrates data at scale, connecting to more than 100 data sources with a centralized data catalog and built-in generative AI capabilities for ETL authoring and Spark troubleshooting.

Official product page

5published use cases

4industries

2countries on record

Generative AI

top AI capability

Evidence mix: High 5 · Medium 0 · Low 0 — bands are computed from each record's evidence signals.

Industry

Country

5 use cases

InsurancePredictive Analytics

Eazy Asigurari Builds an ML-Driven Insurance Pricing Engine on Amazon SageMaker AI

Romanian cloud-native insurer Eazy Asigurari built a proof of concept for a data-driven pricing engine using Amazon SageMaker AI, AWS Glue, Amazon API Gateway, Amazon RDS for PostgreSQL and Amazon DynamoDB. The ML models backtest premiums and highlight potential deviations across thousands of customer segments, with the actuarial team reviewing all ML outputs before informing pricing decisions. The proof of concept was completed within 2 months and the insurer reduced data analysis time by up to 80 percent.

Eazy Asigurari· RomaniaAWS Glue · Amazon API Gateway · Amazon RDS for PostgreSQL +2

HealthcarePredictive AnalyticsDocument IntelligenceGenerative AI

Sanofi Drives Scientific Innovation with AI on AWS for Real-Life Patient Impact

Paris-based Sanofi's Digital Accelerator built eight AI-powered products on AWS in 18 months, including a marketing suite deployed across 18 countries, using Amazon SageMaker for ML development and condensing advanced analytics processes that took 6 months down to 1 month.

Sanofi· FranceAmazon SageMaker · Amazon SageMaker Studio · AWS Lambda +7

CybersecurityAgentic AIGenerative AI

CyberArk combines Apache Iceberg and Amazon Bedrock AI agents to cut support case resolution time up to 95%

CyberArk redesigned its technical support pipeline using AWS Fargate, PyIceberg and Amazon Bedrock (Claude 3.7 Sonnet) to auto-generate grok patterns for parsing diverse vendor log formats into Iceberg tables, and built autonomous AI agents that query Athena and CyberArk's knowledge base to perform root-cause analysis from natural-language questions. The system cut case resolution time by up to 95% (complex cases from up to 15 days to 2-4 hours), let engineers handle up to 4x more cases per day (from 2-3 to 8-12), and made logs queryable within minutes instead of hours or days.

CyberArkAmazon Bedrock · Apache Iceberg · AWS Fargate +5

InsuranceGenerative AIMachine LearningPredictive Analytics

Building a central data, analytics, and AI solution using AWS with Generali

Insurance and asset management group Generali built a central data, analytics and AI solution on AWS to standardize AI adoption across its more than 40 operating entities, using Amazon Redshift for the central data warehouse, AWS Glue for data-quality and transformation pipelines, Amazon SageMaker AI to automate claim settlement and predictive payout modeling, and Amazon Bedrock to power a generative AI customer-assistance agent providing instant responses. The company developed 16 flagship AI use cases spanning pricing, underwriting, claims processing and operations, deployable across operating entities via a centralized Global AI engine, while complying with GDPR and internal governance policies.

GeneraliAmazon Bedrock · Amazon SageMaker AI · Amazon Redshift +1

Life SciencesDocument IntelligenceRetrieval-Augmented GenerationAgentic AI

Novartis: Accelerating Drug Development with AI-Powered Clinical Trial Transformation

Novartis partnered with AWS Professional Services and Accenture to modernize their drug development infrastructure and integrate AI across clinical trials, with the goal of reducing trial development cycles by at least six months. The initiative built a GXP-compliant data mesh platform on AWS with Databricks for processing, enabling AI use cases including protocol generation and an intelligent decision system (digital twin). Early results from the patient safety domain showed 72% query speed improvements, 60% storage cost reduction, and 160+ hours of manual work eliminated. The protocol generation use case achieved 83-87% acceleration in producing compliant protocols.

NovartisAmazon Web Services (AWS) · Databricks · Amazon S3 +8