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Expedite your Genesys Cloud Amazon Lex bot design with the Amazon Lex automated chatbot designer

AWS Machine Learning

Machine learning (ML) technologies continually improve and power the contact center customer experience by providing solutions for capabilities like self-service bots, live call analytics, and post-call analytics. To assist those who may be starting with a blank canvas, Amazon Lex provides the Amazon Lex automated chatbot designer.

Chatbots 111
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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. The following is an example of a prompt used in VitechIQ: """You are Jarvis, a chatbot designed to assist and engage in conversations with humans.

Chatbots 119
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Guest Blog: 10 Chatbot Features That Make Your Bot More Helpful to Customers

Comm100

Chatbots are quickly becoming a long-term solution for customer service across all industries. A good chatbot will deliver exceptional value to your customers during their buying journey. But you can only deliver that positive value by making sure your chatbot features offer the best possible customer experience.

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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. Step 3 – The Lambda function stores the query image in Amazon S3 with a specified ID.

Chatbots 118
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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. First, the user logs in to the chatbot application, which is hosted behind an Application Load Balancer and authenticated using Amazon Cognito.

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How Q4 Inc. used Amazon Bedrock, RAG, and SQLDatabaseChain to address numerical and structured dataset challenges building their Q&A chatbot

AWS Machine Learning

Enterprises turn to Retrieval Augmented Generation (RAG) as a mainstream approach to building Q&A chatbots. The end goal was to create a chatbot that would seamlessly integrate publicly available data, along with proprietary customer-specific Q4 data, while maintaining the highest level of security and data privacy.

Chatbots 115
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Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning

For example, if you have want to build a chatbot for an ecommerce website to handle customer queries such as the return policy or details of the product, using hybrid search will be most suitable. Contextual-based chatbots – Conversations can rapidly change direction and cover unpredictable topics.

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