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

AWS Machine Learning

In the first part of the series, we showed how AI administrators can build a generative AI software as a service (SaaS) gateway to provide access to foundation models (FMs) on Amazon Bedrock to different lines of business (LOBs). It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker.

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Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

SaaS 136
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Enhance deployment guardrails with inference component rolling updates for Amazon SageMaker AI inference

AWS Machine Learning

For more information about the SageMaker AI API, refer to the SageMaker AI API Reference. 8B-Instruct to DeepSeek-R1-Distill-Llama-8B, but the new model version has different API expectations. In this use case, you have configured a CloudWatch alarm to monitor for 4xx errors, which would indicate API compatibility issues.

APIs 88
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Secure a generative AI assistant with OWASP Top 10 mitigation

AWS Machine Learning

These steps might involve both the use of an LLM and external data sources and APIs. Agent plugin controller This component is responsible for the API integration to external data sources and APIs. The LLM agent is an orchestrator of a set of steps that might be necessary to complete the desired request.

APIs 93
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Integrate SaaS platforms with Amazon SageMaker to enable ML-powered applications

AWS Machine Learning

A number of AWS independent software vendor (ISV) partners have already built integrations for users of their software as a service (SaaS) platforms to utilize SageMaker and its various features, including training, deployment, and the model registry.

SaaS 83
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Model customization, RAG, or both: A case study with Amazon Nova

AWS Machine Learning

Fine-tune an Amazon Nova model using the Amazon Bedrock API In this section, we provide detailed walkthroughs on fine-tuning and hosting customized Amazon Nova models using Amazon Bedrock. We first provided a detailed walkthrough on how to fine-tune, host, and conduct inference with customized Amazon Nova through the Amazon Bedrock API.

APIs 98
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Transforming credit decisions using generative AI with Rich Data Co and AWS

AWS Machine Learning

Its software-as-a-service (SaaS) solution empowers leading banks and lenders with deep customer insights and AI-driven decision-making capabilities. They provide access to external data and APIs or enable specific actions and computation. This post is co-written with Gordon Campbell, Charles Guan, and Hendra Suryanto from RDC.