Remove Chatbots Remove Construction Remove Self service
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Deploy self-service question answering with the QnABot on AWS solution powered by Amazon Lex with Amazon Kendra and large language models

AWS Machine Learning

Powered by Amazon Lex , the QnABot on AWS solution is an open-source, multi-channel, multi-language conversational chatbot. This includes automatically generating accurate answers from existing company documents and knowledge bases, and making their self-service chatbots more conversational.

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Delight your customers with great conversational experiences via QnABot, a generative AI chatbot

AWS Machine Learning

Enterprises with contact center operations are looking to improve customer satisfaction by providing self-service, conversational, interactive chat bots that have natural language understanding (NLU). Users of the chatbot interact with Amazon Lex through the web client UI, Amazon Alexa , or Amazon Connect.

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Add conversational AI to any contact center with Amazon Lex and the Amazon Chime SDK

AWS Machine Learning

In traditional contact centers, one solution for long hold times is enabling self-service options for customers using an Interactive Voice Response system (IVR). With Amazon Lex , you can build powerful, multi-lingual conversational AI systems and elevate the self-service experience for your customers with no ML skills required.

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Accenture creates a Knowledge Assist solution using generative AI services on AWS

AWS Machine Learning

Accenture has integrated this generative AI functionality into an existing FAQ bot, allowing the chatbot to provide answers to a broader array of user questions. Using this context, modified prompt is constructed required for the LLM model. Several webpages were ingested into the Amazon Kendra index and used as the data source.

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Self-Driving Cars and Self-Service Contact Centers: How Close are We?

Vistio

Also, they contained no information on traffic jams, construction, or weather conditions. Robotic Process Automation (RPA), chatbots, workflow engines, Natural Language Processing (NLP), and Artificial Intelligence (AI)—the list goes on. How much further to your destination? How long would it take to get there? When would you need gas?

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SLAs For Today’s Contact Center

Fonolo

Ultimate Guide to SLAs That Work New Considerations: Adapting SLAs to Modern Realities Advancements in AI and automation should also find you questioning one-size-fits-all service level agreements. For starters, the advent of chatbots and improved self-service means agents are often dealing with more complex problems.

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Machine Learning or Linguistic Rules: Two Approaches to Building a Chatbot

Aspect

For a company that is trying to decide whether to use chatbots to serve customers, those questions matter. In customer service, pretty much everything starts with a question: “What is my balance?”. The Machine Learning Chatbot Approach. The Linguistic Rules Chatbot Approach. It’s also the technology’s biggest excuse.