Default intents

Two intents are created automatically when you create an agent:

• Default welcome intent: matched when an end-user begins a conversation with your agent.
• Default fallback intent: matched when your agent doesn't match an end-user input to any other intents.

Default welcome intent

The default welcome intent is matched when an end-user begins a conversation with your agent. It should return a response that lets end-users know what your agent does or what end-users can say to begin a conversation. You should customize the pre-populated intent responses for your agent.

The default welcome intent is matched in one of two ways:

• One of its training phrases are matched, which are pre-populated with common greetings, like "hello".
• This intent has a welcome event attached to it, which is triggered when the end-user begins a conversation with your agent via a supported integration.

Default fallback intent

The default fallback intent is matched when your agent doesn't match an end-user input to any other intents.

This intent is not matched if an audio input doesn't contain any transcribed speech.

This intent is automatically configured with a variety of static text responses, like "I didn't get that. Can you say it again?".

You can customize fallback intents by changing the pre-populated text responses or by adding negative examples.

You can also create additional fallback intents:

1. Go to the Dialogflow ES console.
2. Select an agent.
3. Select Intents in the left sidebar menu.
4. Click the option more_vert button at the top of the intents page.
5. Select Create Fallback Intent.

Fallback intent responses

You can change the pre-populated text responses, but they should communicate to the end-user that their input was not recognized.

Negative examples

You can add training phrases to fallback intents that act as negative examples. There may be cases where end-user expressions have a slight resemblance to your training phrases, but you do not want these expressions to match any normal intents.

For example, a room booking service may have a training phrase like "I'd like to book a room". If the end-user wants to purchase a book about rooms, they may say "I'd like to buy a book about rooms." To ensure that the end-user expression does not match your intent, you can add that phrase as a negative example.