Q&A: Fuuz Founder Craig Scott on AI and the Future of Fleet Management

If the advent of Artificial Intelligence (AI) computing in trucking has you feeling overwhelmed, don’t worry. You’re not alone. But Craig Scott, founder and CEO of Fuuz by MFGx, says AI is a powerful operating system that can be applied to virtually any management stream and deliver powerful boosts in efficiency, transparency and communication.

Scott and his engineering team at MGFx developed the Fuuz software platform with AI capabilities based on his background in manufacturing. And he says the system can be applied to any part of a trucking company’s business – including route and cargo optimization, maintenance, parts and inventory management, and more.

In this interview with HDT, Scott explains why AI is so powerful, and why it’s best to look at AI systems as all-encompassing technology that can be quickly and easily applied to any management problem.

HDT: Let’s start from a very high view: Fuuz isn’t a specialized software solution. It works in many different applications, correct?

Scott: Right. It can be used in many commercial applications. It is management software powered by Artificial Intelligence.  And it can be extended to meet specific business needs. In the transportation industry, it can help you manage distribution, special deliveries, parts inventory, core exchanges, brokering, payroll, maintenance and even weight balancing cargo and cubing out trailers. It can gather real-time data from assets out on the road and immediately put that information to use in your operations. It’s a very powerful tool.

HDT: What’s the difference between machine learning systems, which many fleet managers are familiar with, and an AI system like Fuuz?

Scott: Machine learning systems have been around for quite a while. AI is much newer. They are very different systems – although there are some similarities between the two. Machine learning has been around since computers were invented. It’s not a new concept. A set of programs evaluate data, and then, based on that data analyzes trends for the user. When it comes to predictive maintenance, machine learning can look at the miles on a group of trucks and compare that to a component failure. And it can make a prediction based on that data that tells you the optimal time to replace that component before a failure occurs. Pretty straightforward.

HDT: But AI goes deeper?

Scott: Right. Because AI is more about language models that train the AI processing engine. This enables AI to deal with much more abstract issues. Machine learning is very point specific. A truck runs 60,000 miles and needs new brake linings. Easy. AI’s power comes into play when you have a massive amount of information. AI can be trained to interpret that data. It does this by understanding the unique significance of specific words and events. It can look at historical events as well. So what you get is more of a real-time, right-now decision maker for your business. AI can learn on the fly and help you deal with issues immediately.

HDT: Can you give us an example of how AI would do that?

Scott: Sure. Let’s say you have Fuuz as the overlying AI engine for your maintenance management system. And Fuuz scans the web and learns that the Commercial Vehicle Safety Alliance Annual Brake Check week is scheduled to begin in the next month. AI can immediately go into your maintenance system and make brake inspections a priority. It can also instruct your technicians to replace marginal brake linings ahead of schedule to ensure the truck is compliant if it gets inspected.

HDT: Fleets are already getting a firehose of data off trucks and, increasingly, from connected components on trucks. Can Fuuz help cut through all the chatter and focus on what’s important?

Scott: Yes. That is a lot of what Fuuz does. But it’s far more powerful than that. At Fuuz, we developed a system that can handle a number of different scenarios that affect your business. You can use it to optimize trailers for weight over volume, for example. You can use it to automatically load cargo into trailers based on deliveries on the route. Or you can use it to load cargo with unusual, or odd, shapes and sizes. We have one fleet client that hauls large LED light poles and they use Fuuz to analyze the cargo’s dimensions in 3D and create a geometric pattern to load a trailer for optimal space usage and efficiency in loading and unloading.

HDT: So, AI truly is next-level computing for pretty much any management situation? 

Scott: AI is going to give fleet managers power like they’ve never imagined. We’re talking about what is really the next stage of the industrial revolution. It’s that significant of a technology. We’ve had computing systems that process information and give us answers based on data. But AI is a system that does the thinking about the data, as well. AI can process far more information, far faster than a human can. And that capability can help you bring efficiencies to any system you need to monitor and manage. 

HDT: What can fleets do to learn more about the practical applications of AI?

Scott: At Fuuz, we’re happy to help. We have demonstration videos on our website available and we’re happy to have a conversation with anyone interested in learning more about this technology. Moving beyond that, we can consult with fleets on implementing AI. And we have use cases we share that show the value these systems offer.