Remove APIs Remove Customer Support Remove Enterprise
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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

Generative AI has transformed customer support, offering businesses the ability to respond faster, more accurately, and with greater personalization. AI agents , powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses.

APIs 131
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Generative AI operating models in enterprise organizations with Amazon Bedrock

AWS Machine Learning

Generative AI can revolutionize organizations by enabling the creation of innovative applications that offer enhanced customer and employee experiences. To facilitate this, the centralized account uses API gateways or other integration points provided by the LOBs AWS accounts.

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How Customer Support Software Enhances Business Efficiency and Customer Satisfaction?

Wowdesk Blog

Research shows that 86% of buyers are willing to pay more for a great customer experience, and companies that prioritize customer support software see up to 60% higher profits. With the rapid digital transformation, businesses must adopt the best customer support software to enhance efficiency and satisfaction.

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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 125
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Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart

AWS Machine Learning

With the advent of these LLMs or FMs, customers can simply build Generative AI based applications for advertising, knowledge management, and customer support. You can use this post as a reference to build secure enterprise applications in the Generative AI domain using AWS services.

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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

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. While the SageMaker Canvas UI offers a code-free visual interface, the APIs empower developers to interact with these features programmatically.

APIs 122
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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning

Lets say the task at hand is to predict the root cause categories (Customer Education, Feature Request, Software Defect, Documentation Improvement, Security Awareness, and Billing Inquiry) for customer support cases. You are a Support Agent and an expert on the enterprise application software. client = boto3.client("bedrock-runtime",

Education 113