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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data APIs to create more personalized and effective customer support experiences. An automotive retailer might use inventory management APIs to track stock levels and catalog APIs for vehicle compatibility and specifications.

APIs 131
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Amazon Bedrock launches Session Management APIs for generative AI applications (Preview)

AWS Machine Learning

Amazon Bedrock announces the preview launch of Session Management APIs, a new capability that enables developers to simplify state and context management for generative AI applications built with popular open source frameworks such as LangGraph and LlamaIndex. Building generative AI applications requires more than model API calls.

APIs 123
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Tool choice with Amazon Nova models

AWS Machine Learning

However, as use cases have matured, the ability for a model to have access to tools or structures that would be inherently outside of the models frame of reference has become paramount. This could be APIs, code functions, or schemas and structures required by your end application. Amazon Nova will use the weather tool.

APIs 107
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Orchestrate an intelligent document processing workflow using tools in Amazon Bedrock

AWS Machine Learning

We demonstrate how generative AI along with external tool use offers a more flexible and adaptable solution to this challenge. The solution uses the FMs tool use capabilities, accessed through the Amazon Bedrock Converse API. For more details on how tool use works, refer to The complete tool use workflow.

APIs 99
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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

Many businesses want to integrate these cutting-edge AI capabilities with their existing collaboration tools, such as Google Chat, to enhance productivity and decision-making processes. The custom Google Chat app, configured for HTTP integration, sends an HTTP request to an API Gateway endpoint.

APIs 125
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Implement human-in-the-loop confirmation with Amazon Bedrock Agents

AWS Machine Learning

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the users request. This differs from confirmation flows where the agent directly executes API calls.

APIs 122
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Build a Multi-Agent System with LangGraph and Mistral on AWS

AWS Machine Learning

By using the power of LLMs and combining them with specialized tools and APIs, agents can tackle complex, multistep tasks that were previously beyond the reach of traditional AI systems. Whenever local database information is unavailable, it triggers an online search using the Tavily API.

APIs 130