Extracting data from a conversation

You can create and update entities from the preview console of the Pega Intelligent Virtual Assistant (IVA) and then update the text analytics model with this information. You then map the extracted entity values into case properties, creating a richer and more conversational experience for the end user.

Before you begin: Perform the following tasks for an IVA channel:

Add a conversation to a case type. For more information, see Adding a conversation to a case type.
Add suggested cases for an IVA. For more information, see Adding suggested cases for a conversational channel.

Define new entities for use by your chatbot.
For more information, see Creating entities for an IVA.
Link entities to the properties of a case type.
For more information, see Mapping entities in conversation text.

What to do next: Make the IVA learn from the corrected topics and validated entities by building the text analytics model.