Normalized claim
Response time reduction: 70% decrease
70 percent reduction in response times
El Ezaby accelerates pharmacy consultations with EzBot on AWS (generative AI chatbot with Bedrock + RAG)
Use case typePatient engagementUpdated Jun 13, 2026
El Ezaby is an Egyptian pharmacy chain with more than 400 branches. Its pharmacists rely on the company academy and senior doctors for guidance on complex cases, but retrieving advice from a 500,000-file knowledge base was slow and difficult.
- Organization
- El Ezaby
- Industry
- Healthcare
- Location
- Egypt
- Published
- June 2026
Reported outcomes
3x
issues resolved without human interventionAutomation & deflection
−70%response time reduction+50%user satisfaction improvement−25%operational workload reduction
Strategic outcomes
New product / capabilityLaunched a trusted AI pharmacy chatbotCustomer experience & trustImproved pharmacy guidance qualitySpeed & agilityAccelerated access to medical adviceScale & capacityResolved more issues without human help
Catalog median for automation & deflection deployments: +49% across 19 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
User satisfaction improvement: 50% increase
50 percent improvement in user satisfaction scores
Normalized claim
Issues resolved without human intervention: 3 x increase
3-times increase in the number of issues that can be resolved without human intervention
Normalized claim
Operational workload reduction: 25% decrease
25 percent reduction in the customer team's operational workloads
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- El Ezaby
- Provider
- AWS
- Maturity
- Production
- Linked source
- AWS Customer Story
Customer team operational workload fell by 25%
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Generative AI Chatbot
- 2Retrieval Augmented Generation
- 3Pharmacy Support
- Slow and difficult retrieval of trusted medical advice from a large internal knowledge base.
- Need to provide accurate, context-aware pharmacy guidance quickly across hundreds of branches.
- Concern that generative AI could produce inaccurate results in a healthcare setting.
- AWS Partner IT Visionary built EzBot, a generative AI chatbot on AWS.
- The solution uses Amazon Bedrock with Retrieval Augmented Generation to ground answers in verified learning-management-system sources.
- The application runs on Amazon Elastic Container Service behind an Application Load Balancer, and AWS Glue is used for ETL over large and diverse datasets.
- Response times were reduced by 70%.
- User satisfaction scores improved by 50%.
- The number of issues resolved without human intervention increased 3x.
- Customer team operational workload fell by 25%.
Architecture
EzBot is a generative AI chatbot built with Amazon Bedrock and Retrieval Augmented Generation to ground responses in El Ezaby's verified academy and LMS sources. The chatbot is deployed on Amazon Elastic Container Service behind an Application Load Balancer, with AWS Glue handling ETL for building the data foundation.
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: Jun 8, 2026Publisher: AWSEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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