AWS Machine Learning Blog
Category: Amazon Lex
Drive efficiencies with CI/CD best practices on Amazon Lex
Let’s say you have identified a use case in your organization that you would like to handle via a chatbot. You familiarized yourself with Amazon Lex, built a prototype, and did a few trial interactions with the bot. You liked the overall experience and now want to deploy the bot in your production environment, but […]
Build an appointment scheduler interface integrated with Meta using Amazon Lex and Amazon Connect
This blog post is co-written with Nick Vargas and Anna Schreiber from Accenture. Scheduling customer appointments is often a manual and labor-intensive process. You can utilize advances in self-service technology to automate appointment scheduling. In this blog post, we show you how to build a self-service appointment scheduling solution built with Amazon Lex and Amazon […]
Integrate Amazon Lex and Uneeq’s digital human platform
In today’s digital landscape, customers are expecting a high-quality experience that is responsive and delightful. Chatbots and virtual assistants have transformed the customer experience from a point-and-click or a drag-and-drop experience to one that is driven by voice or text. You can create a more engaging experience by further augmenting the interaction with a visual […]
Use Amazon Lex to capture street addresses
Amazon Lex provides automatic speech recognition (ASR) and natural language understanding (NLU) technologies to transcribe user input, identify the nature of their request, and efficiently manage conversations. Lex lets you create sophisticated conversations, streamline your user experience to improve customer satisfaction (CSAT) scores, and increase containment in your contact centers. Natural, effective customer interactions require […]
Enhance the caller experience with hints in Amazon Lex
We understand speech input better if we have some background on the topic of conversation. Consider a customer service agent at an auto parts wholesaler helping with orders. If the agent knows that the customer is looking for tires, they’re more likely to recognize responses (for example, “Michelin”) on the phone. Agents often pick up […]
Use custom vocabulary in Amazon Lex to enhance speech recognition
In our daily conversations, we come across new words or terms that we may not know. Perhaps these are related to a new domain that we’re just getting familiar with, and we pick these up as we understand more about the domain. For example, home loan terminology (“curtailment”), shortened words, (“refi”, “comps”), and acronyms (“HELOC”) […]
Integrate ServiceNow with Amazon Lex chatbot for ticket processing
Conversational interfaces (or chatbots) can provide an intuitive interface for processes such as creating and monitoring tickets. Let’s consider a situation in which a recent hire on your team is required to cut tickets for office equipment. To do so, they have to interact with a ticketing software that the organization uses. This often requires […]
Build a virtual credit approval agent with Amazon Lex, Amazon Textract, and Amazon Connect
Banking and financial institutions review thousands of credit applications per week. The credit approval process requires financial organizations to invest time and resources in reviewing documents like W2s, bank statements, and utility bills. The overall experience can be costly for the organization. At the same time, organizations have to consider borrowers, who are waiting for […]
Manage dialog to elicit Amazon Lex slots in Amazon Connect contact flows
Amazon Lex can add powerful automation to contact center solutions, so you can enable self-service via interactive voice response (IVR) interactions or route calls to the appropriate agent based on caller input. These capabilities can increase customer satisfaction by streamlining the user experience, and improve containment rates in the contact center. In both the self-service […]
Interpret caller input using grammar slot types in Amazon Lex
Customer service calls require customer agents to have the customer’s account information to process the caller’s request. For example, to provide a status on an insurance claim, the support agent needs policy holder information such as the policy ID and claim number. Such information is often collected in the interactive voice response (IVR) flow at […]