Normalized claim
Cost reduction: 40% decrease
reduced its costs by 40% using Kubernetes
iFood uses Amazon Bedrock to build a virtual waiter and applies Amazon SageMaker for delivery improvements
Use case typeCustomer service automationUpdated Jun 13, 2026
iFood is a Latin American online food delivery platform serving more than 300,000 restaurants and millions of orders each month. The company established an internal AI team and uses AWS services to standardize implementations, improve customer experience, and support AI-driven innovation across ordering, delivery, and fraud prevention workflows. iFood built a virtual waiter named Garçon using Amazon Bedrock, including fine-tuning mentioned by the company, and uses Amazon SageMaker to improve delivery service-level agreements, bolster security, and enhance customer and restaurant experiences. The company also trains internal teams through AWS Training and Certification to build machine learning, architecture, and security skills.
- Organization
- iFood
- Industry
- Consumer & Food
- Location
- Brazil
- Published
- May 2026
Reported outcomes
Cost reduction: −40%
Cost savings
Request throughput: Up to 60 million requests per minute
Catalog median for cost savings deployments: −40% across 171 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Request throughput: 60 million requests per minute
process up to 60 million requests per minute
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- iFood
- Provider
- AWS
- Maturity
- Unknown
- Linked source
- AWS Customer Stories
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 3 of 5
- 1Customer Service
- 2Operational Efficiency
- 3Fraud Detection
- Established the iFood Artificial Intelligence team to accelerate innovation.
- Built the Garçon virtual waiter chat experience with Amazon Bedrock.
- Used Amazon SageMaker to improve delivery SLAs, bolster security, and enhance experiences for customers and restaurants.
- Upkilled internal teams through AWS Training and Certification.
- Used Amazon EKS to process high request volumes in the platform environment.
- The case study says iFood reduced costs by 40% using Kubernetes on AWS.
- The platform processes up to 60 million requests per minute.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: May 27, 2026Publisher: AWSEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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