Conversational AI pre-trained to specific vertical industries is the fastest way to build and launch new self-service experiences.

In the past few years, AI has made a significant impact on the way we interact with technology. Users can now engage across multiple different device types using natural language, which offers a more seamless and intuitive experience when compared to traditional point-and-click interfaces. This shift in how people interact with their devices has led to an increased demand for conversational AI solutions across all industries. Law offices, plumbing companies, and local governments are all looking at ways to enhance their digital self-service tools.

 

Conversational AI powers digital self-service solutions like intelligent search and intelligent virtual assistants. These are often implemented to address an acute pain point for the user or the organization. They could be considered as solutions in response to rising customer service calls due to difficulty finding information on a website (painful for the user and expensive for the organization) or a decrease in available employees to manage inbound live chat queries. Regardless of the initial cause, once a decision is made to solve the problem with conversational AI technology, the desire is to implement quickly and seamlessly.

 

Large organizations will sometimes opt to build from scratch as part of a broader investment in conversational AI. That often means standing up internal development, analytics, and user experience groups dedicated to the function. In organizations without the desire or budget for in-house expertise, it can be much more difficult to find the resources to invest in building conversational AI experiences from scratch while staying on budget and on time. 

 

At XAPP AI, we believe that the best way to build quickly and seamlessly, is by starting with pre-trained conversational models. These pre-trained conversational models can leverage industry specific data sets and AI algorithms to allow for faster deployment, with less hiccups after implementation. 

 

To put it simply, building from scratch is like opening a box and finding a bunch of blocks with no instructions. Building with a pre-trained model is like opening a box and finding those same blocks…but with detailed diagrams and instructions, and some pre-assembled foundations to help you get started.

With pre-trained models, you can skip the initial training phase and get your chatbot up and running quickly—in as little as a few hours.

Some may approach pre-trained models with some skepticism. This is especially true in industries with a lot of specialized jargon and a history of high touch, human to human connection. Their unique requirements can be tough to manage effectively with a standard, “one size fits all” model. It was mentioned earlier that pre-trained conversational models can leverage industry specific data sets. That ability is actually one of the most powerful options available. 

Language has a lot of nuance and different words have different meanings depending on the context of the industry vertical.

 

With budgets continuing to shrink and timetables for technology deployments getting tighter, a great way to build really strong experiences is to use pre-trained conversational models that are specific to a vertical industry

 

Take for example the word, “gear.” If you repair bicycles it means one thing and if you sell outdoor apparel, it means something entirely different.

 

If the conversational model that you’re using is not trained to your specific jargon and use cases, it increases the likelihood that a user won’t be able to find what they’re looking for. When this happens, they’ll either opt for human support or they’ll abandon their efforts entirely. Both of these options cost organizations money.

 

Using pre-trained conversational AI models will put you on third base instead of in the batter’s box. There’s no thinking up all of the different words and scenarios you might encounter. Instead, any effort put in can be focused on customization to meet specific branding or business specifications. To give some more context on how much efficiency you gain from pre-trained models, XAPP AI was able to build 500 custom conversational AI solutions in just 60 days, using Optimal Conversation™ Studio.

 

That’s more than eight brand and business specific conversational AI solutions each day. A from-scratch build can take weeks or months. Using pre-trained conversational models specific to your industry is the most efficient and effective way to get new digital self-service experiences live.

Contact us to discuss how we can help any size business launch Conversational AI experiences that people want to use.


* These fields are required.

October 27, 2022

How Pre-trained Conversational Models by Vertical Industry Deliver Faster Time-to-Market

Building a conversational AI model from scratch is like opening a box and finding a bunch of blocks with no instructions. Building with a pre-trained model is like opening a box and finding those same blocks…but with detailed diagrams and instructions, and some pre-assembled foundations to help you get started.
October 11, 2022
People wearing surgical masks sit at computers in a call center

Three Ways Conversational AI Can Improve the Digital Citizen Experience

Conversational AI offers a scalable way for state and local government agencies to offer more personalized services and interactions in a way that is accessible and intuitive to citizens. It has the ability to work quietly in the background, powering great experiences by improving the consistency and accuracy of information provided, improving speed of response, and improving the intuitiveness and ease of use of the digital experience.
September 27, 2022
Time lapse photo of a train moving quickly down the tracks in a city at night

The Fastest Way to Launch Conversational AI Experiences at Scale

Conversational Artificial Intelligence is changing how we interact with technology and each other. The technology enables more human-like interactions than ever before but the complexities of the technology can make implementation intimidating, especially for organizations looking to implement quickly and often. Our advice to anyone looking for the fastest way to launch conversational AI experiences at scale: find yourself a partner.
September 19, 2022

Surefire Local and XAPP AI partner to help SMBs

Surefire Local and XAPP AI partner to help SMBs improve lead flow and sales efficiency Surefire Local and XAPP AI announce AI-powered conversational site search and chat solutions for […]
September 13, 2022
Photo of a woman's back walking up stone steps

The Step by Step Guide to Evaluating Conversational AI Software for Self-Service

As companies look to integrate conversational AI solutions into their existing tech stacks, it can be difficult to understand how to prioritize ever-evolving customer expectations against the needs of the business, as they relate to this technology. It's hard to determine whether or not the conversational AI solution you're considering will be able to flex and scale as needed. To do this the right way, it’s important to ask a few key questions before you build.
August 25, 2022
Butterfly hangs from a cocoon on a tree branch

Transforming Customer Experience with Conversational AI

It's no secret that customers seek out and become more loyal to companies that offer better experiences. In the digital world, they want answers to their questions and solutions to their problems quickly and easily, without having to go through the click-and-scroll rigamarole we've all grown used to when using online content. While some businesses have responded by adding live chat tools to lend support, many have limited hours and long wait times. Over the years, a new option has emerged: self-service tools and Intelligent Virtual Assistants (IVAs) powered by Conversational AI technologies that let humans talk to computers the way they would talk to another human. To do this the right way, it’s important to ask a few key questions before you build.
August 9, 2022
Young child looks to the sky through a homemade telescope while wearing a wizard cape and hat

What is Intelligent Search?

The benefits of a well executed IVA can range from lowered operating costs to improved conversion rates and the ability to use conversational data to help guide future site or app improvements. The key part of that sentence is “a well executed IVA” because all of the technology in the world means nothing if it doesn’t benefit the user in some way. To do this the right way, it’s important to ask a few key questions before you build.
July 26, 2022
Photo of a cork board with hand written cards affixed with push pins that say, "Human-Oriented Company" and "People First"

Five Things to Consider Before Building an Intelligent Virtual Assistant

The benefits of a well executed IVA can range from lowered operating costs to improved conversion rates and the ability to use conversational data to help guide future site or app improvements. The key part of that sentence is “a well executed IVA” because all of the technology in the world means nothing if it doesn’t benefit the user in some way. To do this the right way, it’s important to ask a few key questions before you build.
July 14, 2022
Overhead view of a person facing a laptop which is displaying a webpage with a large search bar under the title, "Find Anything"

Three Tips to Supercharge On-Site Search

One of the most valuable digital tools your organization can offer is a robust on-site search function. When done properly, on-site search can provide powerful insight into your users' needs and help you tailor content to meet those needs. By focusing on three key areas, you can improve the value of your on-site search implementation.