In some industries, putting your technology front and center is a good way to build excitement and attract new customers. But in logistics, where independent operators outnumber their corporate counterparts and business is built on relationships, asking each customer to learn a new way of doing business is more or less out of the question.
Fraight AI, a freight brokerage startup based in Chicago, wants to revolutionize the industry with artificial intelligence. But if its founders have their way, most customers won’t be able to tell the difference.
“From our customer’s perspective, we are exactly like other freight brokers,” said co-founder and CTO Zeke Nierenberg (pictured right). “Truck drivers don’t have to download an app, and people don’t even have to know they’re working with something tech-enabled. But we use natural language processing, artificial intelligence and machine learning to automate a lot of repetitive communication.”
The price of shipping any specific category of goods changes constantly, due to factors like supply, demand, gas prices, time of year, weather and the day of the week. To stay apprised of the current price of shipping, traditional freight brokerages employ large numbers of entry-level employees who communicate with logistics providers on a daily basis. That job, said Nierenberg, could just as easily be done by AI-powered chatbots.
“There’s a lot of critical thinking and problem solving required,” he said. “We’re trying to have the critical thinking be the human’s job, instead of having them function as very slow ethernet cables, passing data along.”
In addition to increasing efficiency, Fraight hopes to reduce the risk of having to hire and fire brokers due to market volatility.
“The number one risk for companies is the ability to scale up and down,” said CEO Parker Holcomb (pictured right). “You can’t take someone off the street and have them be a functional broker the next day.”
Beyond rate negotiations and fielding customer inquiries, Fraight’s founders want to use AI to analyze and enhance internal business processes. For instance, by having an overview of all of its ongoing conversations, the company will be able to assess the state of its sales pipeline and make predictions about future needs. It also wants to analyze chat patterns to predict fraud risks.
Still in the early stages of training its AI models, the startup’s processes still involve a lot of human touch. The platform runs every text response it generates by a company representative before sending. The next phase, said Nierenberg, will be to only require approval messages below a certain confidence level threshold.
Images via Shutterstock and Fraight.