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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

Amazon Q Business , a new generative AI-powered assistant, can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in an enterprises systems. 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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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle. It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. As a result, building such a solution is often a significant undertaking for IT teams.

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

AWS Machine Learning - AI

By implementing this architectural pattern, organizations that use Google Workspace can empower their workforce to access groundbreaking AI solutions powered by Amazon Web Services (AWS) and make informed decisions without leaving their collaboration tool. This request contains the user’s message and relevant metadata.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

An example is a virtual assistant for enterprise business operations. This architecture workflow includes the following steps: A user submits a question through a web or mobile application. The architecture of this system is illustrated in the following figure. Similarly, Amazon Bedrock can route requests between Metas Llama 3.1

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

We walk through the key components and services needed to build the end-to-end architecture, offering example code snippets and explanations for each critical element that help achieve the core functionality. You can invoke Lambda functions from over 200 AWS services and software-as-a-service (SaaS) applications.

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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

Solution overview This section outlines the architecture designed for an email support system using generative AI. The following diagram provides a detailed view of the architecture to enhance email support using generative AI. The workflow includes the following steps: Amazon WorkMail manages incoming and outgoing customer emails.