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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning

They have structured data such as sales transactions and revenue metrics stored in databases, alongside unstructured data such as customer reviews and marketing reports collected from various channels. or “Were there any supply chain issues that could have affected our North American market for clothing sales?”

APIs 107
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Generate user-personalized communication with Amazon Personalize and Amazon Bedrock

AWS Machine Learning

For instance, as a marketing manager for a video-on-demand company, you might want to send personalized email messages tailored to each individual usertaking into account their demographic information, such as gender and age, and their viewing preferences. This usually comes from analytics tools or a customer data platform (CDP).

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

AWS Machine Learning

Amazon Q Business enables users in various roles, such as marketers, project managers, and sales representatives, to have tailored conversations, solve problems, generate content, take action, and more, all through a web-based interface. We provide the service account with authorization scopes to allow access to the required Gmail APIs.

APIs 120
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From innovation to impact: How AWS and NVIDIA enable real-world generative AI success

AWS Machine Learning

And now leading our data and AI go-to-market, I hear customers consistently emphasize what they need to transform their domain advantage into AI success: infrastructure and services they can trustwith performance, cost-efficiency, security, and flexibilityall delivered at scale. times lower latency compared to other platforms.

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How Marubeni is optimizing market decisions using AWS machine learning and analytics

AWS Machine Learning

Working with renewable power assets requires predictive and responsive digital solutions, because renewable energy generation and electricity market conditions are continuously changing. This solution helps market analysts design and perform data-driven bidding strategies optimized for power asset profitability.

Marketing 101
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Speed up your time series forecasting by up to 50 percent with Amazon SageMaker Canvas UI and AutoML APIs

AWS Machine Learning

As an example, time-series forecasting allows retailers to predict future sales demand and plan for inventory levels, logistics, and marketing campaigns. In this post, we describe the enhancements to the forecasting capabilities of SageMaker Canvas and guide you on using its user interface (UI) and AutoML APIs for time-series forecasting.

APIs 120
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Syngenta develops a generative AI assistant to support sales representatives using Amazon Bedrock Agents

AWS Machine Learning

Agent architecture The following diagram illustrates the serverless agent architecture with standard authorization and real-time interaction, and an LLM agent layer using Amazon Bedrock Agents for multi-knowledge base and backend orchestration using API or Python executors. Domain-scoped agents enable code reuse across multiple agents.

Sales 109