What challenges did Bayer China face before AI implementation?

Traditional medical representative training was time-consuming, costly, and insufficiently customizable. Bayer China needed a secure and compliant generative AI framework with traceability for training content and interaction data.

What was the impact of the AI solution?

The system saved 6,000 to 7,000 hours of training time for 1,000 medical representatives and trainers. Role-play coaching efficiency improved by more than 50%. The solution went from PoC to launch in 72 days. It reached 450 users at launch and expanded to more than 1,000 users within 6 months.

Source

Bayer China reshapes medical representative training with generative AI on AWS

Updated Jun 13, 2026

Bayer China built Dr. Bei, an LLM-based AI training system for pharmaceutical medical representatives. The system uses conversational AI to simulate doctors for natural-language voice interactions across 14 visit scenarios, improving training flexibility, realism, and compliance. AWS services support the solution with Amazon Bedrock, Amazon Lambda, Amazon API Gateway, and Amazon Landing Zone.

Organization: Bayer China
Industry: Pharma
Location: China
Published: June 2026

Reported outcomes

+50%

role-play coaching efficiency increaseProductivity & throughput

6,000 hours per yeartraining time saved7,000 hours per yeartraining time saved (upper bound)72 daystime to launch450 usersusers reached at launch1,000 usersusers reached in 6 months

Strategic outcomes

New product / capabilityBuilt an AI training systemCustomer experience & trustImproved training realism and flexibilityRisk & complianceStrengthened training compliance and traceabilitySpeed & agilityAccelerated launch from PoC to production

Catalog median for productivity & throughput deployments: +45% across 225 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 3

1Training assistant
2Role-play coaching
3Employee enablement

Traditional medical representative training was time-consuming, costly, and insufficiently customizable.
Bayer China needed a secure and compliant generative AI framework with traceability for training content and interaction data.

Dr. Bei was built as an intelligent conversational bot on Claude via Amazon Bedrock.
Amazon Lambda provides serverless scaling and Amazon API Gateway manages traffic for concurrent use.
Amazon Landing Zone is used to manage access and support the compliance framework.

Technologies

Amazon Bedrock Amazon Lambda Amazon API Gateway Amazon Landing Zone

The system saved 6,000 to 7,000 hours of training time for 1,000 medical representatives and trainers.
Role-play coaching efficiency improved by more than 50%.
The solution went from PoC to launch in 72 days.
It reached 450 users at launch and expanded to more than 1,000 users within 6 months.

Architecture

Dr. Bei is an LLM-based conversational training system built on Claude through Amazon Bedrock. Amazon Lambda provides elastic serverless scaling to support 450 to 1,000 concurrent users, Amazon API Gateway manages traffic during peak request periods, and Amazon Landing Zone supports secure access management and compliance controls.

Sources & evidence1

Groundedness: 5/5Type: Customer StoryPublished: Jun 8, 2026Publisher: AWSEvidence: PrimaryConfidence: High

Primary source

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Customer evidence