AWS Machine Learning Blog

Category: Amazon Lex

Analyzing and optimizing Amazon Lex conversations using Dashbot

This post is co-written by Arte Merritt, co-founder and CEO of Dashbot. In their own words, “Dashbot is an analytics platform for chatbots and voice skills that enables enterprises to increase engagement, satisfaction, and conversions through actionable insights and tools.” After you have deployed a bot, it is critical to analyze bot interactions, learn from […]

Capturing and validating alphanumeric identifiers in Amazon Lex

Enterprises often rely on unique identifiers to look up information on accounts or events. For example, airlines use confirmation codes to locate itineraries, and insurance companies use policy IDs to retrieve policy details. In customer support, these identifiers are the first level of information necessary to address customer requests. Identifiers are typically a combination of […]

Building a business intelligence dashboard for your Amazon Lex bots

You’ve rolled out a conversational interface powered by Amazon Lex, with a goal of improving the user experience for your customers. Now you want to track how well it’s working. Are your customers finding it helpful? How are they using it? Do they like it enough to come back? How can you analyze their interactions […]

Using Amazon Lex Conversation logs to monitor and improve interactions

As a product owner for a conversational interface, understanding and improving the user experience without the corresponding visibility or telemetry can feel like driving a car blindfolded. It is important to understand how users are interacting with your bot so that you can continuously improve the bot based on past interactions. You can gain these […]

Building an AR/AI vehicle manual using Amazon Sumerian and Amazon Lex

Auto manufacturers are continuously adding new controls, interfaces, and intelligence into their vehicles. They publish manuals detailing how to use these functions, but these handbooks are cumbersome. Because they consist of hundreds of pages in several languages, it can be difficult to search for relevant information about specific features. Attempts to replace paper-based manuals with […]

Designing conversational experiences with sentiment analysis in Amazon Lex

To have an effective conversation, it is important to understand the sentiment and respond appropriately. In a customer service call, a simple acknowledgment when talking to an unhappy customer might be helpful, such as, “Sorry to hear you are having trouble.” Understanding sentiment is also useful in determining when you need to hand over the […]

Managing multi-topic conversation flows with Amazon Lex Session API checkpoints

In daily conversations, you often jump back and forth between multiple topics. For example, when discussing a home improvement project related to new windows and curtains, you might have questions like, “How about closing out on curtain styles and then revisiting colors?” When AWS launched Amazon Lex Session API, you learned how to address such […]

Managing conversation flow with a fallback intent on Amazon Lex

Ever been stumped by a question? Imagine you’re in a business review going over weekly numbers and someone asks, “What about expenses?” Your response might be, “I don’t know. I wasn’t prepared to have that discussion right now.” Bots aren’t fortunate enough to have the same comprehension capabilities, so how should they respond when they […]

Authenticate users with one-time passwords in Amazon Lex chatbots

Today, many companies use one-time passwords (OTP) to authenticate users. An application asks you for a password to proceed. This password is sent to you via text message to a registered phone number. You enter the password to authenticate. It is an easy and secure approach to verifying user identity. In this blog post, we’ll […]