The Journey to the Touchless Load

AI implementation is transforming freight technology in many ways, even without significant investment. 

Jesse Buckingham, founder of Vooma, joined Mary O’Connell on Check Call to discuss how AI workflow tools can take on many of the tedious tasks of daily operation.

Buckingham spent much of his career in the logistics ecosystem and knows firsthand what goes into moving freight from point A to point B at scale. 

“It’s been pretty hard traditionally to put tools in place that move the needle on a lot of the tedious things that operators in logistics are doing every day, like track and trace, check calls, building loads in a TMS, and scheduling appointments,” Buckingham said. 

These menial workflows are critical for actually executing freight operations, Buckingham says, but take a lot of taxing time and energy. 

“Most people who got into logistics fell in love with it because of the problem-solving and building relationships with shippers,” Buckingham said. “Like when a train truck breaks down, and there’s a factory relying on that shipment and you’ve got to think on your feet to get something working.” 

Building loads in a TMS and handling other mundane administrative tasks, of course, are vital parts of the industry, but they take a lot of focus away from the more complex issues.

“We really started Vooma as a way to try to build AI workers and workflow tools that could take a lot of that work off people’s plate so that they could do more meaningful work, do the stuff that they love, and be able to focus on the stuff that moves the needle for the business,” Buckingham said. 

In the few years since Vooma launched, the platform has grown and evolved, but the core principles remain the same. Vooma’s cofounder, Mike Carter, previously worked with self-driving trucks and was a founding engineer at Kodiak Robotics. 

“He came from a different angle of logistics where he was focused on automating the driving of the trucks, and we’ve come together to try to build workers that can sit alongside the operators today to automate the tedious tasks that go into moving freight,” Buckingham said.

Buckingham says that he spends a lot of time on brokerage floors and often asks the representatives what they love most about the work. 

“They usually love solving new problems, because every day is different,” he said. That, and of course the relationships that people build in the industry.

It’s the exceptions to the tedious work, Buckingham says, that make up the work most people are much more interested in doing. 

Talking to brokers and other logistics professionals, Buckingham noticed that some of the common frustrations included things like load building, digging into multiple systems to quotes loads, and verifying data across multiple platforms. 

“We started almost three years ago with load building automation, because this was something that universally pretty much everyone was spending a lot of time on,” Buckingham said. That kind of work isn’t just time-consuming, he says, but also mentally taxing. 

“When you think about building a shipment, you might need thirty data points that need to be one-hundred percent correct before you schedule appointments and try to cover a load,” Buckingham said. Repeatedly checking every single field and making sure that it’s all correct adds a lot of stress to the workload.

“I remember chatting with an executive at a top brokerage who said, ‘Building loads sucks,’” Buckingham said. He says that load building automation was a great entry point for Vooma, because it was something that could immediately free up many college educated, skilled employees who had been spending inordinate amounts of time combing through emails and documents just to enter shipments into a TMS.

“We started there with that painful problem, solved that really well, and then from there expanded out into other parts of the workflow,” Buckingham said. “We moved onto quoting, then scheduling downstream, and now we’re helping cover loads and track freight as well,” he said.

Because Vooma focused on finding an entry point and solving the problem of load building, Buckingham says, the company was able to build trust and relationships with clients over time and earn the right to solve more problems.

Now, there are other use cases for Vooma’s platform. They now also do business on the carrier side of the industry.

“Folks will be posting loads onto the loadboard, and their phones blow up,” Buckingham said. “They only get to maybe forty percent of those calls, and a lot of them don’t lead to business, meanwhile there are great carriers sitting on hold or that drop off the call together, and you miss out on covering the load with the best fit truck.” Whitewater Freight experienced this exact challenge – their 10-person team was fielding 2,900 calls weekly, nearly three per minute, with 50% coming from unqualified carriers. After implementing Vooma, they now book 86% of their posted loads without adding headcount.

According to Buckingham, he’s spoken to many brokers who are at the precipice of adding another shipper, but aren’t sure they have the team in place to even be able to handle that volume of incomings calls required to cover the freight. That’s another area Vooma sees as an opportunity to handle workflow for the best employees.

“How do you give people extensions that can handle the monotonous blocking and tackling so they can continue to handle more and more revenue-generating business?” Buckingham asked. 

While AI automations aren’t going to be able to perfectly solve all these problems in the near future, he says, they can greatly increase the share of daily tasks that can be handled seamlessly. Sunset Transportation’s 6% increase in spot shipment win rate and ability to automatically track 120 quotes per rep daily demonstrates this impact.

What makes transportation challenging to automate, according to Buckingham, is that it involves so many nuanced exceptions. Handling those exceptions with AI depends on building up knowledge over time. 

“I think it will be a journey where a lot depends on being able to make sure that the system can learn and understand a lot of the nuance that goes into daily decisions,” Buckingham said. “Eventually, you can start to reduce what is an exception and have your systems handle more and more of those edge cases. That’s collective intelligence,” he said. 

Vooma built its systems with that in mind. They’re designed so that representatives train the AI workers in the same way that they might train a new employee. This approach has already shown results – at Whitewater Freight, new reps who previously needed weeks of one-on-one mentorship can now quote independently in just days, with one new hire recently quoting with zero hand-holding.

“A lot of employees have insights about how to do something well, but that knowledge isn’t always transferable,” Buckingham said. “Sometimes when someone is promoted or leaves for another company, a certain amount of knowledge is completely lost. It’s not always well propagated across an organization.” 

“One of the best things about the kinds of systems we’re building is that you can almost instantly realize the benefits of that training across the organization, and then that process of optimizing various roles can compound much faster,” Buckingham said. “You don’t have those scenarios where someone does a great job and then moves into another role without being able to properly train their counterparts.” 

Buckingham says that this compounded learning effect is only going to get more and more powerful as various AI systems continue to learn nuances and interact with other systems. 

Creating profiles of behaviors and preferences for the various carriers and shippers you work with, for instance, is something that Vooma’s AI systems can help with in a way that simply wasn’t available prior to AI integration.

“Before, that data was often being recorded, but it wasn’t typically meaningfully available to any systems,” Buckingham said. “The AI can be trained on relatively fuzzy anecdotes and still create a cohesive picture based on the data that’s available.”

Sometimes, the AI can even learn those types of details about a carrier without being prompted, simply from learning in context, according to Buckingham. 

Despite the capabilities, some operators are cautious about adopting AI. Some teams see it as an opportunity, but others are concerned about new training, employee replacement, or adjusting to new systems. Buckingham says that executives who want to adopt AI can mitigate a lot of that trepidation with the right messaging. 

“It’s important to communicate to your teams that this is how the industry is evolving, and the future demands that we all learn new tools and practices,” Buckingham said. He says that it’s vital to make a point of involving people in that process with support, training, and feedback. 

“Some of our best implementations are the ones where the business is clear about its objectives but has cultivated a lot of buy-in by creating a culture where people are excited about change and better workflows,” Buckingham said. “After you choose a vendor, you also have to choose champions in your organization that adopt new tools and get others on board with using them.”

“You can’t underestimate the value of putting some runs on the board and showing case studies of what success looks like,” Buckingham said. “You can show people how their jobs will be improved, how they can make more money, and how they can do more meaningful work with new tools,” he said.

Click here to learn more about Vooma.