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Conversational Analytics: Powerful Data Behind Business Transformation

InMoment XI

When you analyze the natural language interactions between customers and an organization, conversational analytics unlocks a wealth of insights that can be used to resolve issues faster, enhance agent performance, reduce costs, and demonstrate the value of customer service investments. What is Conversational Analytics?

Analytics 195
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Create a multimodal chatbot tailored to your unique dataset with Amazon Bedrock FMs

AWS Machine Learning

With recent advances in large language models (LLMs), a wide array of businesses are building new chatbot applications, either to help their external customers or to support internal teams. This may be useful for later chat assistant analytics. Such a multimodal assistant can be useful across industries.

Chatbots 120
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Vitech uses Amazon Bedrock to revolutionize information access with AI-powered chatbot

AWS Machine Learning

Vitech helps group insurance, pension fund administration, and investment clients expand their offerings and capabilities, streamline their operations, and gain analytical insights. Data store Vitech’s product documentation is largely available in.pdf format, making it the standard format used by VitechIQ.

Chatbots 122
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How Deltek uses Amazon Bedrock for question and answering on government solicitation documents

AWS Machine Learning

Question and answering (Q&A) using documents is a commonly used application in various use cases like customer support chatbots, legal research assistants, and healthcare advisors. This includes a one-time processing of PDF documents. The steps are as follows: The user uploads documents to the application.

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The Health of the Contact Center: Are You Ready for 2019?

A survey of 1,000 contact center professionals reveals what it takes to improve agent well-being in a customer-centric era. This report is a must-read for contact center leaders preparing to engage agents and improve customer experience in 2019.

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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning

Such data often lacks the specialized knowledge contained in internal documents available in modern businesses, which is typically needed to get accurate answers in domains such as pharmaceutical research, financial investigation, and customer support. This task involves answering analytical reasoning questions.

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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. Now, employees at Principal can receive role-based answers in real time through a conversational chatbot interface.

Financial 120