Call Center Agent Assistant - Amazon Lex

This documentation is for Amazon Lex V1. If you are using Amazon Lex V2, refer to the Amazon Lex V2 guide instead. We recommend using Amazon Lex V2 to take advantage of the latest features.

Call Center Agent Assistant

In this tutorial, you use Amazon Lex with Amazon Kendra to build an agent assist bot that assists customer support agents and publish it as a web application. Amazon Kendra is an enterprise search service that uses machine learning to search through documents to find answers. For more information about Amazon Kendra, see the Amazon Kendra Developer Guide.

Amazon Lex bots are widely used in call centers as the first point of contact for customers. A bot is often capable of resolving customer questions. When a bot can't answer a question, it transfers the conversation to a customer support employee.

In this tutorial, we create an Amazon Lex bot that agents use to answer customer queries in real time. By reading the answers that the bot provides, the agent is spared from looking up answers manually.

The bot and web application that you create in this tutorial helps agents respond to customers efficiently and accurately by quickly providing the right resources. The following diagram shows how the web application works.

            Customer talking to a support agent. Amazon Lex keeps track of the conversation and calls 
            the Kendra Search Intent if the customer asks a question, which then searches an index of 
            documents stored in Amazon S3. Amazon Kendra finds the answer and returns it to Amazon Lex, which then 
            displays the answer to the agent.

As the diagram shows, the Amazon Kendra index of documents is stored in an Amazon Simple Storage Service (Amazon S3) bucket. If you don't already have an S3 bucket, you can set one up when you create the Amazon Kendra index. In addition to Amazon S3, you will use Amazon Cognito for this tutorial. Amazon Cognito manages permissions for deploying the bot as a web application.

In this tutorial, you create an Amazon Kendra index that provides answers to customer questions, create the bot and add intents that allow it to suggest answers based on the conversation with the customer, set up Amazon Cognito to manage access permissions, and deploy the bot as a web application.

Estimated time: 75 minutes

Estimated cost: $2.50 per hour for an Amazon Kendra index and $0.75 for 1000 Amazon Lex requests. Your Amazon Kendra index continues to run after you are finished with this exercise. Be sure to delete it to avoid unnecessary costs.

Note: Make sure that you choose the same AWS Region for all the services used in this tutorial.