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

AWS Machine Learning

Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training techniques such as instruction fine-tuning and reinforcement learning from human feedback.

Analytics 127
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Improve LLM performance with human and AI feedback on Amazon SageMaker for Amazon Engineering

AWS Machine Learning

The team navigates a large volume of documents and locates the right information to make sure the warehouse design meets the highest standards. The Amazon D&C team implemented the solution in a pilot for Amazon engineers and collected user feedback. During the pilot, users provided 118 feedback responses.

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How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale

AWS Machine Learning

Organizations can search for PII using methods such as keyword searches, pattern matching, data loss prevention tools, machine learning (ML), metadata analysis, data classification software, optical character recognition (OCR), document fingerprinting, and encryption. This speeds up the PII detection process and also reduces the overall cost.

APIs 115
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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. QnABot is a multilanguage, multichannel conversational interface (chatbot) that responds to customers’ questions, answers, and feedback.

Chatbots 121
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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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NEW: MindTouch Customer Experience Analytics

Mindtouch

When customers engage with your company’s product documentation and self-service support knowledge, they’re doing so much more than viewing a single piece of content. What is MindTouch Customer Experience Analytics? They’re sending valuable signals about their experience. Self-Service Report.

Analytics 101
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Sentiment Analysis on Customer Feedback: A Guide to Enhance Customer Experience

Lumoa

By leveraging sentiment analysis on customer feedback, businesses can understand and dig deep into the emotions of their customers, allowing them to identify and address pressing concerns, and fine-tune their products and services. In This Article: Why is Sentiment Analysis on Customer Feedback Important?

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Study: The Health of the Contact Center

What does it take to engage agents in this customer-centric era? Download our study of 1,000 contact center agents in the US and UK to find out what major challenges are facing contact center agents today – and what your company can do about it.

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The Challenges of Omnichannel: Why so Many Contact Centers Struggle with Digital Self-Service

To find how contact centers are navigating the transition to omnichannel customer service, Calabrio surveyed more than 1,000 marketing and customer experience leaders in the U.S. about their digital customer communication strategies. Read the report to find out what was uncovered.

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Executive Report: The Customer Data Too Often Overlooked by the C-Suite

A recent Calabrio research study of more than 1,000 C-Suite executives has revealed leaders are missing a key data stream – voice of the customer data. Download the report to learn how executives can find and use VoC data to make more informed business decisions.