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Google has recently announced the enterprise edition of Dialogflow, its Chatbot API.

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:

  • Natural language Understanding, allows quick extraction and response of a user’s intent to implement natural and rich interactions between users and businesses.
  • Over 30+ pre-built agents for quick and easy identification of custom entity types.
  • An integrated code editor, to build native serverless applications linked with conversational interfaces through Cloud Functions for Firebase.
  • Integration with Google Cloud Speech,  for voice interactions, support in a single API
  • Cross-Platform and Multi-Language Agent, with 20+ languages supported over 14 different platforms.

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.

Content Marketing Editor at Packt Hub. I blog about new and upcoming tech trends ranging from Data science, Web development, Programming, Cloud & Networking, IoT, Security and Game development.

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