What challenges did iFood face before AI implementation?

Deliver individualized customer experiences at iFood's scale. Optimize internal developer work and fraud prevention across high-volume order flows.

What was the impact of the AI solution?

Supported personalization and fraud prevention across more than 80 million monthly orders. A purchase through the app goes through more than 100 AI models. Enabled AI-driven optimization of internal developer work.

Rank#250of 3,449

Source

Evidence: Medium50/100

iFood: AI journey with AWS for personalization and fraud prevention

Use case typeCustomer personalizationUpdated Jul 15, 2026

iFood, one of Brazil's largest delivery marketplaces, uses AWS generative AI to personalize the customer experience and support internal developer workflows. The company operates at very high scale, with more than 80 million orders per month across 330,000 partner establishments. iFood also applies AI-driven fraud prevention across the purchase flow, with users going through more than 100 AI models when buying through the app.

Organization: iFood
Industry: Retail
Location: Brazil
Published: July 2026

Reported outcomes

330 thousand establishments

partner establishmentsOther quantified impact

80 million ordersmonthly orders100 modelsAI models in purchase flow

Strategic outcomes

Customer experience & trustPersonalized the ordering experience at scaleRisk & complianceApplied AI-driven fraud prevention in the app purchase flowEmployee experienceOptimized internal developer work

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Monthly orders: 80 million orders increase

AWS Solutions Case StudyJul 15, 2026Customer storyExplicit claimMedium evidence strength

more than 80 million orders per month

Normalized claim

Partner establishments: 330 thousand establishments increase

AWS Solutions Case StudyJul 15, 2026Customer storyExplicit claimMedium evidence strength

with deliveries from more than 330,000 partner establishments

Normalized claim

AI models in purchase flow: 100 models increase

AWS Solutions Case StudyJul 15, 2026Customer storyExplicit claimMedium evidence strength

they go through more than 100 AI models

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: iFood
Provider: AWS
Maturity: Unknown
Linked source: AWS Solutions Case Study

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1Customer personalization
2Fraud detection
3Developer productivity

Deliver individualized customer experiences at iFood's scale.
Optimize internal developer work and fraud prevention across high-volume order flows.

Used Amazon SageMaker and Amazon S3 as the AWS foundation for its AI journey.
Applied generative AI to personalize the ordering experience from recommendation through delivery.
Used AI models in fraud prevention processes and to standardize and facilitate implementations.

Technologies

Amazon SageMaker Amazon S3

Supported personalization and fraud prevention across more than 80 million monthly orders.
A purchase through the app goes through more than 100 AI models.
Enabled AI-driven optimization of internal developer work.

Sources & evidence1

Evidence: Medium50/100Evidence strength