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

AWS Machine Learning

AI agents , powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses. In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data APIs to create more personalized and effective customer support experiences.

APIs 129
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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. Customer experience Lets explore how rolling updates work in practice with several common scenarios, using different-sized LLMs. 8B-Instruct to DeepSeek-R1-Distill-Llama-8B, but the new model version has different API expectations.

APIs 107
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Discover insights from Gmail using the Gmail connector for Amazon Q Business

AWS Machine Learning

Performing an intelligent search on emails with co-workers can help you find answers to questions, improving productivity and enhancing the overall customer experience for the organization. This connector allows you to query your Gmail data using Amazon Q Business as your query engine. Choose Enable to enable this API.

APIs 119
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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning

Based on our experiments using best-in-class supervised learning algorithms available in AutoGluon , we arrived at a 3,000 sample size for the training dataset for each category to attain an accuracy of 90%. Sonnet prediction accuracy through prompt engineering. Model access Grant permission to use Anthropics Claude 3.5

Education 110
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Amazon Bedrock Flows is now generally available with enhanced safety and traceability

AWS Machine Learning

Reduced time and effort in testing and deploying AI workflows with SDK APIs and serverless infrastructure. Bedrock Flows makes it easier for developers and businesses to harness the power of generative AI, enabling you to create more sophisticated and efficient AI-driven solutions for your customers.

APIs 120
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How iFood built a platform to run hundreds of machine learning models with Amazon SageMaker Inference

AWS Machine Learning

AI inference at iFood iFood has harnessed the power of a robust AI/ML platform to elevate the customer experience across its diverse touchpoints. In the past, the data science and engineering teams at iFood operated independently. Engineering teams would then struggle to integrate these models into production systems.

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Build generative AI chatbots using prompt engineering with Amazon Redshift and Amazon Bedrock

AWS Machine Learning

Amazon Bedrock offers a choice of high-performing foundation models from leading AI companies, including AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon, via a single API. Prompt engineering makes generative AI applications more efficient and effective.