Learn more >
by Scott D'Angelo | Published August 6, 2019
Artificial intelligenceConversationDeep learningMachine learning
This article is part of the Watson Assistant learning path. See the Watson Assistant page for more information on features and getting started.
With IBM Watson Assistant, you can build conversational interfaces into any application, device, or channel. Most virtual assistants try to mimic human interactions, but Watson Assistant is more. Watson Assistant knows when to search for an answer from a knowledge base, when to ask for clarity, and when to direct you to a human. The following video gives a high-level overview of the Watson Assistant service.
This article is the first part of a learning path that helps you gain a better understanding about how Watson Assistant works, and how you can integrate it with other applications to build your own virtual assistant.
Virtual assistants, or chatbots, go far beyond the gimmicky approach that they are often associated with. You can use bots to set appointments, call a car, and so on. It’s not a replacement for search. Amazon Echo and Google Home are excellent examples of virtual assistants. There is no interface, so having a well-structured dialog to talk through is essential.
A couple of instances of where Watson Assistant excels are customer self-service and employee self-service. Watson Assistant:
The following figure shows Watson Assistant architecture that’s common for all implementations. In this architecture:
Users interact with the assistant through one or more of these integration points:
A virtual assistant that you publish directly to an existing social media messaging platform, such as Slack or Facebook Messenger.
A custom application that you develop, such as a mobile app or a robot with a voice interface.
The assistant receives user input and routes it to the dialog skill.
The dialog skill interprets the user input further, then directs the flow of the conversation. The dialog gathers any information it needs to respond or perform a transaction on the user’s behalf.
Any questions that cannot be answered by the dialog skill are sent to the search skill, which finds relevant answers by searching the company knowledge bases that you configure for the purpose.
A typical approach used when deploying Watson Assistant
This section covers the terms that you need to know as you follow the learning path to use Watson Assistant in your applications.
Watson Assistant is available in both the public and private cloud.
Public Cloud: Watson Assistant is available on IBM Cloud. The Watson Assistant “Getting started tutorial” provides additional information on setting up the service.
Private Cloud: Watson Assistant is also available through IBM Private Cloud, on premises or managed, with IBM Cloud Pak for Data and the Watson Assistant add-on.
There are several SDKs available that support the various AI services. They are not limited to the following list.
The Watson Assistant V1 API is available to help you get started, but we recommend using the Watson Assistant V2 API with your apps.
This article is the first part of a learning path that guides you through the deployment of the Watson Assistant service and using included tools for creating intents, entities, and integrations with other applications. To get a high-level look at Watson Assistant including features and pricing, see the Watson Assistant product page. To continue with the learning path, take a look at the next step in the process, Create your first Assistant-powered chatbot.
Get an overview of Watson Assistant and learn how it can help you use the power of AI to connect…
This learning path gives you an understanding and working knowledge of Watson Assistant. It explains the basics of the service…
Build a fun treasure hunt game that uses visual recognition.
Back to top