AI startup helps tackle logistics nightmares

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Sometimes it seems that the weight of the current problems in the global supply chain rests on the containers carried every day by thousands of tractors crossing the US. As consumer demand for everything from shoes to sofas skyrocketed since the start of the Covid-19 pandemic, it became easy to blame the humble truck. After all, more than 70% of all goods shipped in the US, or 10.2 billion tons, were transported by truck last year.

Of course, the supply chain crisis is actually a complex global conundrum with few simple answers. But Optimal Dynamics, an AI-powered startup that announced $33 million in Series B financing last week led by the Westly Group, is helping trucking companies solve their logistics nightmares by automating and optimizing their operations. For example, the solution ensures shippers are transporting the right loads at the right time, the right drivers get the right cargo to the right destination, and helps businesses answer questions about what equipment to buy and how many drivers they need.

“Freight forwarding companies are realizing that they need logistics technology to support decision-making and adapt to changing situations – it is now a requirement, no longer just a nice thing to have,” said Daniel Powell, CEO of Optimal Dynamics, who founded the company in 2016 with his colleagues. father warren. The elder Powell has been on the faculty of Princeton’s Operations Research Department since 1981, at the helm of a research lab that, among other things, developed the first successful platform for optimizing truckloads in the 1980s.

Freight transport receptive to AI technology

“That rich technology grew through many iterations over the decades and matured incredibly,” Powell said. “We were able to leverage our 40-year heritage at Princeton to apply this kind of robust decision automation technology to logistics.”

Twenty years ago, trucking companies started adopting the core databases that are now prevalent, he said, while in the past five years “the biggest push has been around what I generally call high-fidelity data, akin to what the fintech world does.” went through with companies integrated with the banks to provide data.”

Lately, the truck market has become increasingly receptive to logistics technology, he added, including AI. In fact, the market for AI solutions in the global supply chain as a whole is estimated to be worth more than $14 billion by 2028.

In a VentureBeat article published last year, linked to the company’s $18 million Series A funding, Powell said Optimal Dynamics’ “high-dimensional AI” allows them to “absorb exponentially more detail.” as they plan under uncertainty. We also use smart methods that allow us to deploy robust AI systems even if we have very little training data, a common problem in the logistics industry.”

Supply chain issues drive high demand for AI

Now the company is benefiting from remarkably good timing. “It’s just incredible that you see this underlying technology coupled with an environment that can support its implementation, and then there’s the timing of the supply chain that’s basically falling apart,” he said. “It made it a really great ecosystem to deploy this technology at scale and actually help our customers get through this.”

Powell admits that Optimal Dynamics is not the only solution in the truck logistics space, or a comprehensive solution. It competes with Uber Freight and high-value startups, including KeepTruckin, Next Trucking and Convoy. But, he emphasized, “we are a very critical building block to enable this species[s] of large logistics networks to increase efficiency and be more flexible within their operations.”

For example, a customer, Hawk Logistics Solutions, was able to use Optimal Dynamics’ self-service tool to identify a new location within their logistics network where they could hire a large number of drivers. They are also moving into new operating regions based on analysis that showed them new loads that they could move on a daily basis.

“This is data they already have, but they didn’t have the tools to look at the cargo volume they saw on a daily basis and understood there were more efficient ways to do their job,” he said. “Now they’re actually going into what’s called a lane, which is an A to B movement of a truckload, so now they’re operating at a whole new length.”

Large fleets must plan under uncertainty

Although Hawk is a smaller customer, mega-enterprises tend to look for the latest efficiencies within their businesses, enabling more automation than they have in-house.

“One of the things they want from us is to help them plan in times of uncertainty,” Powell explains. “Our system allows them to plan well into the future in uncertain environments with so many changing variables.” Most major customers have internal teams building simulations that can only make decisions about node variables, which is limiting. “With tools that allow them to plan further into the future, they can be more proactive — to say yes to customers sooner, or identify issues within their business as other companies could with a weather warning,” he said.

Many truck customers, he added, are at the very beginning of their AI-powered journey. “We often lay the first data lines,” he said. “It might be the first time they’ve ever set up an automation, a data feed, outside of their company.”

The truck industry will struggle without AI adoption

But trucking companies need to start innovating, he stressed, and the applications that can harness machine learning and AI powerfully offer a major advantage to those operators that do. “There are actually very few companies that have really fundamentally changed their technology and the way they make decisions,” he said. “We see companies with 50 trucks making decisions based on the idea of ​​’that looks good,’ and we see Fortune 500, $5 billion logistics operations making decisions by the seat of their pants.”

It will become increasingly difficult for those companies to compete without AI, he added: “You see that in the industry, with old-school companies closing that aren’t willing to change or adapt quickly enough.”

Yet many organizations are actually further along than they think in terms of what it takes to power an AI-driven system like Optimal Dynamics. “They’ve made the underlying investments to support these types of tools, so we can often teach them that they’re not even five years away, but they’re here today,” Powell said.

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