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ChatGPT – is it the answer to customer service?

CCNG

To work in a customer service environment ChatGPT will always need a well-managed Knowledge Management system for it to retrieve its answers from that allows them to govern the information and have full control of the narrative. Set the foundation for success with a system that delivers answers to customers through any channel.

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The Future of Debt Collection Agencies: Contact Center Technology and Customer-Centric Strategies

NobelBiz

Traditional collection methods, such as persistent phone calls and letters, are making way for more nuanced, technology-driven, and customer-oriented strategies. This evolution reflects broader trends in consumer behavior, regulatory environments, and technological advancements. In the U.S.,

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Preparing Your Business for the API Economy

Nexmo

Partly, that’s code they write themselves but what makes modern software development so effective is that developers can easily build on the work of others through APIs. When you think of APIs it’s likely that some big names come to mind: Nexmo, the Vonage API platform; Stripe for payments; or one of the new Open Banking APIs.

APIs 78
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Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning

Use hybrid search and semantic search options via SDK When you call the Retrieve API, Knowledge Bases for Amazon Bedrock selects the right search strategy for you to give you most relevant results. You have the option to override it to use either hybrid or semantic search in the API.

APIs 106
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Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning

Companies face complex regulations and extensive approval requirements from governing bodies like the US Food and Drug Administration (FDA). Users then review and edit the documents, where necessary, and submit the same to the central governing bodies. This post is co-written with Ilan Geller, Shuyu Yang and Richa Gupta from Accenture.

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Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning

The solution uses AWS Lambda , Amazon API Gateway , Amazon EventBridge , and SageMaker to automate the workflow with human approval intervention in the middle. The approver approves the model by following the link in the email to an API Gateway endpoint. API Gateway invokes a Lambda function to initiate model updates.

APIs 96
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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

MLOps – Model monitoring and ongoing governance wasn’t tightly integrated and automated with the ML models. Reusability – Without reusable MLOps frameworks, each model must be developed and governed separately, which adds to the overall effort and delays model operationalization.