Remove Information Remove Lambda Remove Serverless
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Streamlining Workflows with Feature Branches and Logical Stacks

Xebia

By switching to serverless, you pay for the usage. The CheckoutProcess name describes what it is, a role used by, for example, a lambda function that processes the checkout. The prefix Joris makes it unique and provides information about who owns and created the resource. Simple: In the example, we needed an RDS instance.

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

AWS Machine Learning - AI

The solution presented in this post takes approximately 15–30 minutes to deploy and consists of the following key components: Amazon OpenSearch Service Serverless maintains three indexes : the inventory index, the compatible parts index, and the owner manuals index.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For example, a marketing content creation application might need to perform task types such as text generation, text summarization, sentiment analysis, and information extraction as part of producing high-quality, personalized content. Each distinct task type will likely require a separate LLM, which might also be fine-tuned with custom data.

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

AWS Machine Learning - AI

These meetings often involve exchanging information and discussing actions that one or more parties must take after the session. Organizations typically can’t predict their call patterns, so the solution relies on AWS serverless services to scale during busy times.

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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. API Gateway is serverless and hence automatically scales with traffic. Some applications may need to access data with personal identifiable information (PII) while others may rely on noncritical data.

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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

Manual processes and fragmented information sources can create bottlenecks and slow decision-making, limiting teams from focusing on higher-value work. The chat agent bridges complex information systems and user-friendly communication. This streamlined process enhances productivity and customer interactions across the organization.