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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

However, ingesting large volumes of enterprise data poses significant challenges, particularly in orchestrating workflows to gather data from diverse sources. In this post, we propose an end-to-end solution using Amazon Q Business to simplify integration of enterprise knowledge bases at scale.

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Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning - AI

In this post, we demonstrate how to create an automated email response solution using Amazon Bedrock and its features, including Amazon Bedrock Agents , Amazon Bedrock Knowledge Bases , and Amazon Bedrock Guardrails. These indexed documents provide a comprehensive knowledge base that the AI agents consult to inform their responses.

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

AWS Machine Learning - AI

The solution integrates large language models (LLMs) with your organization’s data and provides an intelligent chat assistant that understands conversation context and provides relevant, interactive responses directly within the Google Chat interface. This request contains the user’s message and relevant metadata.

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Revolutionizing clinical trials with the power of voice and AI

AWS Machine Learning - AI

This is where the integration of cutting-edge technologies, such as audio-to-text translation and large language models (LLMs), holds the potential to revolutionize the way patients receive, process, and act on vital medical information. These insights can include: Potential adverse event detection and reporting.

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

AWS Machine Learning - AI

AI agents , powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses. Amazon Bedrock Agents coordinates interactions between foundation models (FMs), knowledge bases, and user conversations.

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Build a gen AI–powered financial assistant with Amazon Bedrock multi-agent collaboration

AWS Machine Learning - AI

The use of a multi-agent system, rather than relying on a single large language model (LLM) to handle all tasks, enables more focused and in-depth analysis in specialized areas. The primary agent can also consult attached knowledge bases or trigger action groups before or after subagent involvement.

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Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning - AI

Whether youre an experienced AWS developer or just getting started with cloud development, youll discover how to use AI-powered coding assistants to tackle common challenges such as complex service configurations, infrastructure as code (IaC) implementation, and knowledge base integration.

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