Normalized claim
Account Statements latency reduction: 50% decrease
Latency for the bank’s Account Statements service was reduced by 50 percent
Bank of Georgia accelerates modernization and experiments with generative AI on AWS
Use case typeCloud migrationUpdated Jul 8, 2026
Bank of Georgia migrated to AWS to modernize a monolithic architecture into microservices, improve performance and scalability, and accelerate innovation for its 2.2 million customers. The bank also began experimenting with generative AI using Amazon SageMaker AI and used Amazon OpenSearch Service for search and analytics, while adopting managed services, infrastructure as code, and AWS Direct Connect to support compliance and low latency.
- Organization
- Bank of Georgia
- Industry
- Finance
- Location
- Georgia
- Published
- July 2026
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Service uptime: 100% increase
maintaining 99.99 percent uptime for services deployed on AWS
Normalized claim
Infrastructure provisioning managed as code: 80% increase
implemented infrastructure as code for around 80 percent of its infrastructure provisioning on AWS
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Bank of Georgia
- Provider
- AWS
- Maturity
- Exploring
- Linked source
- AWS Case Study
The bank also began experimenting with generative AI using Amazon SageMaker AI and used Amazon OpenSearch Service for search and analytics, while adopting managed services, infrastructure as code, and AWS Direct Connect to support compliance and low latency
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Cloud migration
- 2Software modernization
- 3AI model training
- Migrated to AWS using managed services and a 4-year cloud adoption plan
- Implemented Amazon Elastic Kubernetes Service for containerized modernization
- Used infrastructure as code for around 80 percent of infrastructure provisioning and AWS Direct Connect for dedicated connectivity
- Started generative AI experimentation with Amazon SageMaker AI and used Amazon OpenSearch Service for agentic AI search and analytics
- Reduced latency for the Account Statements service
- Maintained high uptime on AWS
- Scaled rapidly for customer campaigns
- Improved ability to spin up and test environments quickly
Architecture
Bank of Georgia conducted an infrastructure maturity assessment, created cloud governance/FinOps/product engineering teams, aligned with the AWS Well-Architected Framework, migrated applications using Amazon Elastic Kubernetes Service, used Amazon Direct Connect for dedicated connectivity, and began experimenting with generative AI using Amazon SageMaker AI and Amazon OpenSearch Service.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jul 8, 2026Publisher: AWSEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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