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How Self-Serve Healthcare Technologies Empower Patients

The Northridge Group

Once the patient arrives for their appointment, they’ll need to fill out several documents. Chatbots are also catching on in the healthcare industry. According to recent data, 22% of consumers are twice as likely to use chatbots as other communication channels. You may unsubscribe from these communications at anytime.

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Techniques for Creating Effective Customer Service Scripts for Your Call Center

Global Response

Compliance reminders : Remind agents of relevant legal or regulatory compliance issues, ensuring the conversation meets industry standards. It requires weaving together customer needs, agent capabilities, and the organization’s overarching goals into one comprehensive document. Understand customer needs and expectations.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

Accelerate your security and AI/ML learning with best practices guidance, training, and certification AWS also curates recommendations from Best Practices for Security, Identity, & Compliance and AWS Security Documentation to help you identify ways to secure your training, development, testing, and operational environments.

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How to Evaluate Which Customer Service Channels to Prioritize

aircall

This is because customers can effortlessly refer back to previous messages, send documents and images, and they don’t need to dedicate a part of their day to waiting to speak to a customer support agent. It also offers customers quick replies and lets them share images and documents regarding their inquiries and concerns.

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12 Customer Service Skills to Enhance the Customer Experience

aircall

Despite the many technological advancements in customer service—like the development of chatbots and self-servicing tools—86% of consumers would still rather interact with a real person over a robot. Although what defines “good” customer service may vary from business to business, there are industry standards that you can use as a benchmark.

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Best practices to build generative AI applications on AWS

AWS Machine Learning

Whether creating a chatbot or summarization tool, you can shape powerful FMs to suit your needs. There are several use cases where RAG can help improve FM performance: Question answering – RAG models help question answering applications locate and integrate information from documents or knowledge sources to generate high-quality answers.

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Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

With Knowledge Bases for Amazon Bedrock, you can quickly build applications using Retrieval Augmented Generation (RAG) for use cases like question answering, contextual chatbots, and personalized search. For latest information, please refer to the documentation above.

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