Virtual Assistants

Glossary

The following list provides definitions of commonly used terms in conversation testing. Dynamic Text Marking The dynamic text annotation feature allows you to annotate a section of the text. During test execution, the annotated portion of the text is ignored by the platform for text assertion. To know more, see…

Test Case Execution Summary

The Test Case Execution Summary allows you to view the test case results, identify the failed test cases, and resolve the flow of the virtual assistant. It gives complete details of the overall test results and the defects found. The following sections explain the options available on the Conversation Testing…

Test Case Assertion

A test case assertion is a statement specifying a condition that must be satisfied for a test case to be considered successful. In the context of conversational systems, test case assertions can be used to validate various aspects of the conversation, such as the correctness of the response to a…

Test Editor

You can use the Test Editor to view the test cases and their metadata. This section explains the steps to access the test editor and use the available options: On the Conversation Testing page, click on any Test Suite to go to the Test Editor. In the Test Editor, the…

Create a Test Suite

A Test Suite contains a collection of test cases grouped to simulate a specific conversation between the user and the bot and used anytime for test execution. You can know the execution status and determine and analyze the results in a test suite. In Conversation testing, you can create the…

Conversation Testing Overview

Conversation Testing enables you to simulate end-to-end conversational flows to evaluate the dialog task execution or perform regression. You can create Test Suites to capture various business scenarios and run them at a later time to validate the assistant’s performance. The Conversation testing framework tracks the transition coverage and determines…

Intent Discovery (Beta)

The new Intent Discovery module helps you auto-extract popular intents from previous user conversations. It reduces the time and effort to build a virtual assistant and leads to the success of your Conversational AI Journey. This is a beta feature and is available only for the English language and Enterprise…

Create Custom Dashboard Filters

Prior to the Version 10.0 release, you had to add filter conditions in the ‘Filter by’ clause for individual widgets within a dashboard. There was no provision to filter the records at a dashboard level. The platform now allows you to create custom filters that filter the data for all…

Feedback Analytics

Once you’ve created a Feedback Survey for your conversations based on a survey type (NPS, CSAT, or Like/Dislike), it’s important to constantly monitor and analyze the customer responses, feedback survey scores, and trends over a given period. Thus, knowing the survey type scores and the key metrics for respondents, responses,…

Migrate Google Dialogflow Bot to the XO Platform

The Kore.ai XO Platform supports the migration of an existing Google Dialogflow bot into your XO Platform account using the External NLU Adapter. This easy migration reduces the manual efforts in creating the dialog flow on the XO Platform while allowing you to implement the inbuilt features of Kore.ai on…
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