What challenges did ASKUL face before AI implementation?

Upgrade a core SAP S/4HANA workload while maintaining strict 24/365 e-commerce site availability and minimizing migration risk and downtime. Establish a stable AWS-based data platform to support future AI and automation initiatives.

Source

Proof of conceptEvidence: Medium65/100

ASKUL Uses AWS Infrastructure to Enable AI/Automation with Amazon Q in QuickSight

Use case typeAI platformUpdated Jun 13, 2026

ASKUL, a Japan e-commerce and logistics company, upgraded its core SAP S/4HANA system on AWS while preserving 24/365 availability for its e-commerce operations. The company migrated one of Japan's largest data collections to AWS using Amazon EC2 high-memory instances, Amazon EBS, Amazon VPC, and Amazon CloudWatch. ASKUL has also started trialing natural-language data analysis with Amazon Q in QuickSight as part of a broader platform for AI and automation.

Organization: ASKUL
Industry: Logistics
Location: Japan
Published: May 2026

Planned next steps

The source says the organization aims to achieve Time: 21 hours.
The source says the pilot could deliver: Enabled natural-language data analysis.
The source says the organization aims to achieve: Completed migration within target downtime.

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

Normalized claim

Time: 21 hours

AWS Case StudyMay 13, 2026Customer storyInferred claimMedium evidence strength

Completed the migration in August 2025 with 21 hours of downtime, within the 24-hour target.

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

Customer: ASKUL
Provider: AWS
Maturity: PoC
Linked source: AWS Case Study

Started a proof of concept for natural-language data analysis using Amazon Q in QuickSight

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 4

1Cloud Migration
2Data Platform Modernization
3Business Intelligence

Migrated the SAP S/4HANA environment to AWS using 12TB Amazon EC2 high-memory instances.
Used Amazon EBS, Amazon VPC, and Amazon CloudWatch to support storage, networking, and operations monitoring.
Reduced the ECC data volume from 20TB to 5TB before migration and performed four migration rehearsals to meet the downtime target.
Started a proof of concept for natural-language data analysis using Amazon Q in QuickSight.

Technologies

Amazon EC2 Amazon EBS Amazon VPC Amazon CloudWatch Amazon Q in QuickSight

Reported zero CPU and memory faults after migration and stable ongoing operation.

Sources & evidence1

Evidence: Medium65/100Evidence strength