Ryanair on AWS: customer service and agentic AI with Amazon Bedrock and Amazon Connect
Use case typeAutomotive operations automationUpdated Jun 13, 2026
Ryanair uses AWS to improve employee and customer experiences and support business growth across its airline operations. The article highlights an employee app built with Amazon Bedrock and customer service workflows using Amazon Connect.
Reported outcomes
Strategic outcomes
Employee experienceBuilt an employee productivity appCustomer experience & trustStreamlined customer service interactionsScale & capacitySupported airline growth and scalabilityCustomer experience & trustImproved customer experience at scale
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Ryanair
- Provider
- AWS
- Maturity
- Scaled Production
- Linked source
- AWS Case Study
Improve customer service efficiency and interactions at scale
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Customer service automation
- 2Employee productivity
- 3Agentic AI
- Improve customer service efficiency and interactions at scale.
- Boost employee productivity and satisfaction while supporting airline growth.
- Ryanair built an employee app on Amazon Bedrock to support workforce productivity.
- The company uses Amazon Connect to streamline customer service processes and improve customer interactions.
- Ryanair also continues broader AWS modernization work across its cloud journey, including applications and infrastructure improvements.
Technologies
- The Bedrock-based employee app is described as hugely successful for Ryanair's growth.
- AWS-powered customer service workflows are intended to increase efficiency and improve the customer experience.
- The broader cloud approach supports operational efficiency and business scalability.
Architecture
The article states that Ryanair built an employee app on Amazon Bedrock and uses Amazon Connect for customer service workflows, but it does not provide a detailed architecture diagram or end-to-end technical design.
Sources & evidence1
Evidence: Medium55/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Technical implementation details available
Type: Case StudyPublished: May 13, 2026Publisher: AWS Case StudyEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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