Who can say they enjoy finding answers to questions by using search on a website? Even when the results are relevant, we still have to navigate and read blocks of text to find answers — which might be only one or two words among sentences and paragraphs.

A well-designed chatbot can provide a more friendly experience. Instead of searching, you ask the chatbot a question and it returns a succinct answer. But building one that functions like this has been challenging.

Until now.

We just released a new version of the Watson Assistant Search Skill with short-answer retrieval. This feature…

One of the struggles of building a chatbot is capturing user addresses. While any teenager can understand that “45 Pond Lane, Springfield, MA” is an address with street and city information, it’s surprisingly hard for chatbot to discern the same.

Why is it hard? Consider this address: “4310 Illinois Ave, Somerville, MA”. Because the street portion is the name of a state (“Illinois”) a rules-based algorithm probably would stumble to parse things correctly.

In an earlier article Detecting names and locations with Watson Assistant I introduced the concept of Contextual Entities in Watson Assistant, and illustrated how they can capture…

Humans misspeak all the time. Even though we think we are stating our desires and questions clearly, we often don’t form sentences well, leading others to ask, “Did you actually mean…?” It takes listening skills and intelligence to keep even basic conversations on track.

Now imagine customer care chatbots doing the same thing. In most cases, they can’t. They simply don’t have enough intelligence to detect that the conversation is going off track the way humans would. So they just repeat an answer cheerfully — angering the customer and leading to the spiral of misery and frustration with customer service.

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We recently published a technical paper that demonstrates how Watson Assistant does a better job understanding users than other conversational AI platforms. To achieve this, we use many complex technologies in natural language understanding and machine learning. We’d like to explain in basic terms how they work.

At heart, conversational AI software has to perform three things: understand the user’s question; find the best answer from its training, or search for it through documents; and return an answer in a concise, precise manner. …

Watson Assistant has released two features into general availability that make it even more robust and friendly to customers: an out-of-the-box WhatsApp integration and Session History for Web Chat.

Companies can now use Watson Assistant to help their customers on all the most prominent digital channels. For the past year, we’ve supported web, SMS, Facebook Messenger, and Slack. Today, we are happy to add another very popular channel to the list: WhatsApp!

Authors: J William Murdock, Guy Lev, Michal Shmueli-Scheuer, Jaymin Desai, Anastas Stoyanovsky, Christophe Guittet, Jim Hurne, Ofir Florenz, and David Konopnicki

Sometimes your customers face problems or have questions. It happens — nobody’s perfect. You want to get those customers the answers they need. More and more customers try to find answers by themselves before reaching out to your support service (especially the introverts). That’s good for reducing your costs, if your customers can actually find the answers they are looking for!

A common way to let customers find answers is to have one or more FAQ pages or documents…

As engineers who made Watson Assistant, we know it has the capabilities you need to build highly effective AI solutions for your business. But features alone are not enough. You also need to implement a process to create, analyze, and continuously improve assistants.

This guide will explains our recommendations for an AI lifecycle and the tasks involved in each phase. It’s based on our expertise gained from real world engagements with clients around the world. And now we’ll teach you what we know.

Phases of the AI lifecycle

The AI lifecycle has six phases. The phases are repeated to form an iterative process that you…

We talk a lot about personalizing assistants to your users’ needs, and what’s more personal than speaking in the language they prefer? You can’t deliver a great experience if users struggle to understand your assistant in a non-native language. This guide outline 3.5 (not a typo!) strategies for delivering an assistant that can speak multiple languages.

Strategy 1: Full Machine Translation

Automatic language translation has come a long way in the past decade, but it’s still not perfect. That said, in most cases, it performs more than well enough to get the job done. …