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Amazon chatbot alexa information
Amazon chatbot alexa information








amazon chatbot alexa information

The built-in test features aided the tuning and development process by attributing a matching score to a response. The content designer provided customization options that allowed for organization and readability. They used the AWS open-source Amazon Lex Web UI project, a sample Amazon Lex Web UI that helps provide a full-featured web client for Amazon Lex chatbots.Īfter content was gathered from the campus, creating question and answer responses for the bot was an easy process. Direct users to their website or a human agent on their helpdesk when the bot doesn’t have the answer to a questionĪfter implementing the QnABot to assist agents inside their call center, OSU-OKC decided to extend the bot’s reach to the university’s website.Use the built-in dashboards to see what questions people are asking, making it easy to add new features and functionality as users demand them.Capture user feedback with “Thumbs Up” and “Thumbs Down” responses.Extend the bot using AWS Lambda hooks to fetch dynamic answers from external sources (for more information, see Extending QnABot with Lambda hook functions).Optionally customize the answers by mode for example, use buttons and markdown for a rich web experience, and SSML for a rich voice experience.Integrate the bot with Amazon Kendra to tap into ML-powered enterprise search (for more information, see Using Kendra FAQ for question matching).Use the Content Designer UI to add and edit content to make their bot smarter.Deploy into their AWS account using AWS CloudFormation at the push of a button.The following diagram illustrates the solution architecture.įor OSU-OKC, QnABot simplified bot deployment and administration, allowing even non-technical users to maximize the impact of the solution by allowing them to: They achieved this by automating answers to student FAQs, thereby delivering accurate and up-to-date information, reducing call hold times, and enabling human call center agents to focus on handling higher-value interactions. Deploying QnABot in the call centerĪlthough OSU-OKC’s use of the QnABot evolved throughout 2020, its initial area of focus centered on boosting call center efficiency. The QnABot is an open-source project that uses Amazon Lex to provide a conversational interface for your questions and answers, and can be applied to a host of communication channels, including websites, contact centers, chatbots, collaboration tools like Slack, and Amazon Alexa-enabled devices.

#Amazon chatbot alexa information professional#

With this in mind, OSU-OKC began working with AWS Professional Services in January 2020, and became the first university to deploy a call center using Amazon Connect and the QnABot.Īmazon Connect is a cloud contact center that provides a seamless experience across voice and chat for customers and agents. ML-powered chatbots are dynamic, and help connect with students through the communication channels they prefer, whether that’s a website, phone, chatbot, or by asking an Alexa-enabled device. The team identified conversational chatbots as a way to address the information gap that students face. “Building on that, we also had a real focus on consistency and accuracy of information-it mattered to us that current and future students could rely on the information they were getting across school and faculty communication channels.” “The first thing we wanted to address was the lack of visibility we had into customer sentiment at any given time,” says Michael Widell, Interim President at OKC-OSU. After all, universities need students the same way businesses need customers. They knew that if they could develop a solution that accurately anticipated their students’ needs and delivered timely and relevant information, they could boost their chances of attracting future students.

amazon chatbot alexa information

Oklahoma State University, Oklahoma City (OSU-OKC) recognized this, and was intent on providing a better solution to address student questions using machine learning (ML) technology from AWS. However, like anything new, it also can also bring plenty of questions to answer and obstacles to overcome. For many students, embarking on a higher education journey is an exciting time filled with new experiences.










Amazon chatbot alexa information