Remove Authentication Remove Lambda Remove Scalability
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WordFinder app: Harnessing generative AI on AWS for aphasia communication

AWS Machine Learning - AI

Secure access using Route 53 and Amplify The journey begins with the user accessing the WordFinder app through a domain managed by Amazon Route 53 , a highly available and scalable cloud DNS web service. Secure authentication with Amazon Cognito Before accessing the core features, the user must securely authenticate through Amazon Cognito.

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

AWS Machine Learning - AI

Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic. This request contains the user’s message and relevant metadata.

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Create generative AI agents that interact with your companies’ systems in a few clicks using Amazon Bedrock in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Lets look at an example solution for implementing a customer management agent: An agentic chat can be built with Amazon Bedrock chat applications, and integrated with functions that can be quickly built with other AWS services such as AWS Lambda and Amazon API Gateway. For Authentication method , choose API Keys (Max.

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Building a virtual meteorologist using Amazon Bedrock Agents

AWS Machine Learning - AI

Although weather information is accessible through multiple channels, businesses that heavily rely on meteorological data require robust and scalable solutions to effectively manage and use these critical insights and reduce manual processes. Solution overview The diagram gives an overview and highlights the key components.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices. This scalability allows for more frequent and comprehensive reviews.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. It contains services used to onboard, manage, and operate the environment, for example, to onboard and off-board tenants, users, and models, assign quotas to different tenants, and authentication and authorization microservices.

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Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

AWS Machine Learning - AI

For MCP implementation, you need a scalable infrastructure to host these servers and an infrastructure to host the large language model (LLM), which will perform actions with the tools implemented by the MCP server. We will deep dive into the MCP architecture later in this post.