Remove 2024 Remove Accountability Remove Chatbots
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Top 5 Customer Service & CX Articles for Week of April 29, 2024

ShepHyken

For context, these are the customers who continue to buy from you over and over again, and should account for the majority of your total sales. Retail brands know that brick-and-mortar experiences alone just won’t cut it, nor will insufficient digital experiences that fail to account for the evolving customer experience.

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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning

Introducing Field Advisor In April 2024, we launched our AI sales assistant, which we call Field Advisor, making it available to AWS employees in the Sales, Marketing, and Global Services organization, powered by Amazon Q Business.

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Secure AccountantAI Chatbot: Lili’s journey with Amazon Bedrock

AWS Machine Learning

Small business proprietors tend to prioritize the operational aspects of their enterprises over administrative tasks, such as maintaining financial records and accounting. While hiring a professional accountant can provide valuable guidance and expertise, it can be cost-prohibitive for many small businesses.

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Challenges in Implementing AI and Chatbots for Customer Support

CSM Magazine

One of the hottest topics in 2024 was AI and its influence on nearly every industry. While no one can truly comprehend the extent of the impact it will have, there is no doubt that AI and chatbots for customer support are being embraced by more and more companies. Who will be fixing the issues related to AI and chatbots?

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Answer questions from tables embedded in documents with Amazon Q Business

AWS Machine Learning

On November 21, 2024, Amazon Q Business launched support for tabular search, which you can use to extract answers from tables embedded in documents ingested in Amazon Q Business. Amazon Q Business applications created on or after November 21, 2024, will automatically benefit from the new capability.

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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

Learn how they created specialized agents for different tasks like account management, repos, pipeline management, and more to help their developers go faster. Learn to apply AWS DeepRacer skills to LLMs, explore multi-modal semantic search, and create AI-powered chatbots.

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Build your gen AI–based text-to-SQL application using RAG, powered by Amazon Bedrock (Claude 3 Sonnet and Amazon Titan for embedding)

AWS Machine Learning

Prerequisites To create this solution, complete the following prerequisites: Sign up for an AWS account if you dont already have one. To evaluate the models accuracy and track the mechanism, we store every user input and output in Amazon Simple Storage Service (Amazon S3). Sonnet on Amazon Bedrock. streamlit run app.py