Fine-tune Your Assistant Performance

with in-built testing tools

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Test Your Virtual Assistant

with out-of-the-box handy tools

Interact with your virtual assistant in real-time before you publish – to test recognition, performance, and flow of the conversation for various scenarios. The XO Platform’s in-built tools enable you to try different variations of user prompts to ensure the NLP interpreter is accurately processing these utterances.

How to Test a Intelligent Virtual Assistant

Utterance Testing

Examine how VA responds

to a variety of user inputs

Testing virtual assistants with a good sample of utterances gives invaluable insights into the performance.

Understand how the Kore.ai XO Platform process the user request through its’ multi-engine. Check if it identifies the right intent and entities for a given utterance; fine-tune the training based on the expected response.

Batch Testing

Improve the accuracy

by testing the performance of the ML model

Delineate how well the virtual assistant understands user utterances using predefined test suites available in the builder or custom test suites. Execute a series of tests to get a detailed statistical analysis and gauge the performance of the ML model; view NLP metrics like precision, recall & F1 scores.

Use the Platform’s visualization tools, confusion matrix and K-fold testing to understand the assistant usage patterns, conversation flows and drop-off points.

Further, drill down results to intent and test case level analysis. Tag specific test case results that need follow-up actions and collaborate with your team to improve the performance.

Conversation Testing

Automate Regression Testing

to uncover broken conversations or workflows

Streamline virtual assistant updates confidently by creating conversation test cases for handling regression. You can now create a test by uploading a file. The Flow, Text, and Context assertions test entire flows and allow you to compare versions. The Flow coverage and performance analytics provide helpful insights.

NLU Test Data Suggestions

Achieve Efficient Testing

through advanced test data suggestions

Comprehensive NLU Test Suites

Batch Test suites help evaluate the NLU performance using test datasets. The new Generative AI capabilities analyze IVA scope and generate test data for various scenarios. These test suites help you achieve higher coverage by including unseen phrases, entity checks, spelling mistakes, and negative cases.

Simulate Complex Conversations

The new Generative AI capabilities let you quickly create Conversation Test suites by suggesting possible user responses to simulate conversations for complex scenarios. The platform continuously updates the suggestions as you continue with the conversations.

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Unlock the Black Box

with a fully transparent NLP engine

The Kore.ai XO Platform provides complete transparency into intent identification and entity extraction with explanations about each query response.

The debug log gives you info on what is happening at the backend – you see the NLP, logs, session context, and variables. Unlock the “black box” of machine learning and use the data to analyze the root cause of various failure scenarios.

Health & Monitoring

Diagnose NLP and Conversation Flow Health

within a single intuitive interface

Actionable recommendations suggest essential changes to improve overall NLU and Flow health. The new upgrade includes the entire Flow Health framework. Drill down to specific intents to identify coverage and performance analytics and review uncovered paths to develop new tests.