Dialogflow is Google’s API for building chatbots as well as other conversational interfaces for mobile applications, websites, messaging platforms, and IoT devices. It uses machine learning and natural language processing in the backend to power it’s conversational interfaces. It also has a built-in speech recognition support and features new analytics capabilities.
Now they have extended the API to the enterprises, allowing organizations to build these conversational apps for a large scale usage.
According to Google, Dialogflow Enterprise Edition is a premium pay-as-you-go service. It is targeted at organizations in need of enterprise-grade services that can withstand changes based on user demands. As opposed to the small and medium business owners and individual developers for whom the standard version suffices.
The enterprise edition also boasts of 24/7 support, SLAs, enterprise-level terms of service and complete data protection which is why companies are willing to pay a fee for adopting it.
Here’s a quick overview of the differences between the standard and the enterprise version of Dialogflow:
Source: https://cloud.google.com/dialogflow-enterprise/docs/editions
Apart from this, the API is also a part of Google Cloud. So, it comes with the same support options as provided to cloud platform customers. The enterprise edition also supports unlimited text and voice interactions and higher usage quotas as compared to the free version.
It's Enterprise Edition agent can be created using the Google Cloud Platform Console. Adding, editing or removing entities and intents to the agent can be done using console.dialogflow.com, or with the Dialogflow V2 API.
Here’s a quick glance at some top features:
Uniqlo has used Dialogflow to create their shopping chatbot. Here are the views of Shinya Matsuyama, Director of Global digital commerce, Uniqlo:
“Our shopping chatbot was developed using Dialogflow to offer a new type of shopping experience through a messaging interface, and responses are constantly being improved through machine learning. Going forward, we are also looking to expand the functionality to include voice recognition and multiple languages. ”
According to the official documentation, the project is still in beta stage. Hence, it is not intended for real-time usage in critical applications.
You can learn more about the project along with Quickstarts, How-to guides, and Tutorials here.