Differentiate generative AI applications with your data using AWS analytics and managed databases

This article discusses how organizations can differentiate their generative AI applications by utilizing their own data, in addition to large language models (LLMs) and foundation models (FMs). It presents a framework for implementing generative AI applications enriched and differentiated with an organization's data.

Specifically, the article covers:

• The importance of using company data to provide differential value from generative AI models
• Three key context elements to differentiate generative AI responses: behavioral context, situational context, and semantic context
• A technical architecture using AWS services like Amazon DynamoDB, Amazon OpenSearch Service, Amazon Bedrock, and AWS analytics to implement the framework
• A catalog search use case demonstrating how to augment search capabilities with generative AI and customer data
• Security considerations for implementing such a solution