Transforming Siemens global search with generative AI  powered by AWS

This article discusses how Siemens transformed their global search experience with a generative AI solution built on AWS. It covers the challenges Siemens faced and the innovative solution they implemented.

Specifically, the article covers:

• The need for a personalized and contextual search experience at Siemens
• The challenges of interpreting content from multiple sources while adhering to communication guidelines
• Overview of the serverless, multi-agent architecture on AWS Lambda, Amazon Bedrock, and Amazon API Gateway
• Key AWS services used, including Amazon Bedrock for Large Language Models and Amazon DynamoDB for context retrieval
• The data flow, highlighting agents for validation, intention classification, search, summarization, and guardrails
• Four key learnings: choice of models and services, systematic information gathering for guardrails, effective implementation of guardrails, and validation with automated tests
• Conclusion emphasizing the solution's scalability, compliance, and tailored search experience