A Dialogflow

*agent*

is a virtual agent that handles concurrent conversations with your end-users.
It is a natural language understanding module that understands the nuances of human language.
Dialogflow translates end-user text or audio during a conversation
to structured data that your apps and services can understand.
You design and build a Dialogflow agent to handle the types of conversations required for your system.


A Dialogflow agent is similar to a human call center agent.
You train them both to handle expected conversation scenarios,
and your training does not need to be overly explicit.

Agents also serve as a top-level container for settings and data:

- [Agent settings](https://docs.cloud.google.com/dialogflow/docs/agents-settings) for language options, machine learning settings, and other settings that control the behavior of your agent.
- [Intents](https://docs.cloud.google.com/dialogflow/docs/intents-overview) to categorize end-user intentions for each conversation turn.
- [Entities](https://docs.cloud.google.com/dialogflow/docs/entities-overview) to identify and extract specific data from end-user expressions.
- [Knowledge](https://docs.cloud.google.com/dialogflow/docs/knowledge-connectors) to parse documents (for example, FAQs) and find automated responses.
- [Integrations](https://docs.cloud.google.com/dialogflow/docs/integrations) for applications that run on devices or services that directly handle end-user interactions for you (for example, Google Assistant).
- [Fulfillment](https://docs.cloud.google.com/dialogflow/docs/fulfillment-overview) to connect your service when using integrations.