Easy to build

Train an AI system, no coding skills needed

Training an AI system may seem daunting, but it’s not with Watson Assistant – each topic can be trained with only a few example questions.

Gather information quickly with steps

Say goodbye to complex and brittle decision trees - you can quickly gather information or respond to customers with steps, which you simply prioritize inside of an action.

Recognize plain-language customer responses

Steps use AI under the covers to detect plain-language responses from your customers like synonyms, dates, times, and more – even if they’re misspelled or mispronounced.

Fine-tune the conversation flow with conditions

You get super fine-grained control over the flow of the conversation with an easy-to use condition builder on each step.

Preview actions the way a customer does

As you build, you can preview the conversation as your users will experience it — with advanced debugging capabilities to fix problems quickly.

Build faster by reusing common components

Instead of recreating the same flows in multiple places, you can build a portion of a flow once and reuse it anywhere.

Optimize your assistant with integrations

Complete your assistant with integrations to existing content and CRM systems

Search existing content

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Find up-to-date answers in any existing content, from knowledge bases to websites, with Watson Discovery.

Handoff to live agents

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Deploy anywhere your customers communicate with your business, including web, app, phone or messaging channels.

Integrate across channels

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Easily connect your chatbot platform to existing live agent tools to route customers to the right people in real time.


Frequently asked questions

Does Watson Assistant use machine learning or natural language processing?

Watson is built on deep learning, machine learning and natural language processing (NLP) models to elevate customer experiences and help customers change an appointment, track a shipment, or check a balance. Watson also uses machine learning algorithms and asks follow-up questions to better understand customers and pass them off to a human agent when needed.

Try out the enhanced intent detection model. This new model, which is being offered as a beta feature in English-language dialog and actions skills, is faster and more accurate. It combines traditional machine learning, transfer learning and deep learning techniques in a cohesive model that is highly responsive at run time. For more information, see Improved intent recognition.

How long does building chatbots take?

You can learn how to use the product and build your first topic in less than 30 minutes.

What is an API?

An API is a software intermediary that enables two applications to communicate with each other by opening up their data and functionality. App developers use an API’s interface to communicate with other products and services to return information requested by the end user. When you use an application (such as a virtual assistant) on your phone or computer, the application connects to the Internet and sends data to a server via an API. The API then helps the server interpret the data so it can perform the necessary actions. Finally, the server sends the requested data back to your device via the API where it is interpreted by the application and presented to you in a readable format. Without APIs, many of the online applications that we’ve come to rely on would not be possible.

What is the best way to get started with a visual bot builder interface?

Learn more about how to start building your first chatbot in the Getting started documentation.

Is there a visual chatbot builder tutorial?

Visit the Watson Assistant documentation for a full tutorial on creating your virtual assistant with the visual chatbot builder.

Does Watson Assistant have an out-of-the-box web chat widget?

Yes, you can immediately add your assistant to your company website as a web chat widget that can help your customers with common questions and tasks and transfer customers to human agents. To integrate the web chat widget, follow these instructions to generate and copy the required code onto your webpage(s).

Can I deploy my chatbot to channels like Facebook Messenger, Whatsapp, Slack, or Amazon Alexa?

Yes, you can deploy your chatbot to Facebook Messenger, Intercom, Slack, SMS with Twilio, and WhatsApp. You can even deploy to Amazon Alexa. Learn more about Watson Assistant integrations.

Can I deploy to WordPress?

Yes, you can use this Wordpress plugin (link resides outside IBM). In a few minutes, you can train Watson to answer FAQs, provide useful information and help customers navigate your website.

How do I set up a Twilio account for my chatbot?

To integrate your chatbot with Twilio, you need to add the Watson Assistant phone integration first, then create a Twilio Flex project and a Twilio function to handle incoming calls. Read the full instructions in the Watson Assistant documentation.

Are there chatbot templates to use?

By default, the web chat window shows a home screen that can welcome users and tell them how to interact with the assistant. For information about CSS helper classes that you can use to change the home screen style, see the prebuilt templates documentation.

What are common chatbot use cases?

Customer care is the most common chatbot use case. Chatbots are helpful to both product- and service-based companies looking to provide a superior user experience by to answering customer questions, guiding customers through simple troubleshooting, and connecting customers to the resources they need.

Chatbots are also often used by sales teams looking for a tool to support lead generation. Chatbots can quickly validate potential leads based on the questions they ask, then pass them on to human sales representatives to close the deal.

Chatbots can even be used in e-commerce by acting as a digital sales clerk, akin to what customers would experience in brick-and-mortar stores. E-commerce chatbots can provide a personalized shopping experience that converts passive visitors into engaged prospects.

Try now

Connect with our experts to chat about your customer support use case.