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Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions


Companies across all industries are harnessing the power of generative AI to address various use cases. Cloud providers have recognized the need to offer model inference through an API call, significantly streamlining the implementation of AI within applications. Although a single API call can address simple use cases, more complex ones may necessitate the use of multiple calls and integrations with other services.

This post discusses how to use AWS Step Functions to efficiently coordinate multi-step generative AI workflows, such as parallelizing API calls to Amazon Bedrock to quickly gather answers to lists of submitted questions. We also touch on the usage of Retrieval Augmented Generation (RAG) to optimize outputs and provide an extra layer of precision, as well as other possible integrations through Step Functions.

Introduction to Amazon Bedrock and Step Functions

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from ...


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