How Hapag-Lloyd uses Amazon Bedrock to transform customer feedback into actionable insights

How Hapag-Lloyd uses Amazon Bedrock to transform customer feedback into actionable insights

How Hapag-Lloyd uses Amazon Bedrock to transform customer feedback into actionable insights

https://aws.amazon.com/blogs/machine-learning/how-hapag-lloyd-uses-amazon-bedrock-to-transform-customer-feedback-into-actionable-insights/

Publish Date: 2026-05-05 12:55:00

Source Domain: aws.amazon.com

  • Hapag-Lloyd is a leading liner shipping company with a global presence in over 140 countries, and it employs 14,000 people to maintain extensive operations.
  • The company has a strong focus on digital transformation and innovation through its Digital Customer Experience and Engineering team, with a particular emphasis on becoming AI-native.
  • Hapag-Lloyd has implemented a generative AI-based solution on AWS to automate and transform customer feedback analysis, drastically reducing the time and effort involved in deriving insights from customer comments.
  • The solution uses Amazon Bedrock for AI-powered insights and orchestration, utilizing AWS Lambda, Amazon S3, Amazon OpenSearch Service, and Amazon ECS.
  • The solution includes a chatbot that answers natural language questions by querying the internal OpenSearch index, ensuring responses comply with company security and brand guidelines.
  • Emphasis is placed on responsible AI practices, including programmatic input validation, guardrail policies, and compliance standards to filter harmful content.
  • The company monitors the solution performance using Amazon CloudWatch and ensures the scalability and security of the data pipeline with the help of various AI tools.
  • The AI-driven feedback analytics have been instrumental in guiding product improvements and led to positive user feedback trends, exemplifying the impact of generative AI in enhancing customer experience.
  • The initiative marks the beginning of Hapag-Lloyd’s broader AI-Native Umbrella Program, aiming to provide every department with the tools to responsibly experiment with generative AI applications.