A truck should never wait. Neither should the driver inside it.
Every week, aifleet's software does something no human dispatcher could survive: it weighs roughly 20 quintillion possible ways to route its trucks across 250,000 loads, then picks the combination that keeps the wheels turning and the drivers paid. That number has 19 zeros. Marc Khoury built a company so the people behind the wheel would never have to do the math, or worse, sit idle while someone else fumbled it.
The pitch is deceptively plain. Khoury is the co-founder and CEO of aifleet, a tech-native trucking company headquartered in Austin. It owns trucks. It employs drivers. It hauls full truckloads of freight, the same as half a million other carriers in America. The difference is what happens between loads. In traditional trucking, that gap is dead time: a driver waiting on a call, a truck parked, money evaporating. aifleet treats the gap as a solvable problem and throws AI at it until the gap closes.
Khoury likes to say the quiet part out loud. The industry has spent decades insisting it suffers from a driver shortage. He disagrees, bluntly. Large fleets hire tens of thousands of drivers a year. If the math worked, the seats would stay full. They don't. What looks like a shortage, he argues, is a retention problem wearing a disguise, and retention is downstream of a model that wastes drivers' time and underpays their patience.
The purpose of the company is to optimize our assets, optimize our drivers, create a good livelihood for our drivers and automate as much as possible.
Freight is a $400 billion market with half a million carriers and no center.
"The full truckload market size is $400 billion," Khoury has said, "but it's a massively inefficient and fragmented market with half a million carriers." Fragmentation is the enemy he hunts. When no single operator controls enough trucks to plan at scale, everyone optimizes locally and the whole system leaks value. aifleet's bet is that a fleet run as one coordinated machine, with software booking loads and stacking routes automatically, can out-earn a thousand carriers each guessing on their own.
The early numbers back the thesis. aifleet reports roughly 40% higher truck utilization than the industry average and claims around a fivefold operating profit per truck compared with major carriers. The company grew at 75% to 100% a year, scaling from about 60 drivers in 2022 to several hundred. Spot pricing, the volatile heartbeat of freight, runs automated. Load assignment runs automated. A dispatcher bottleneck simply isn't allowed to form.
Khoury frames the timing as no accident. "We're probably at this inflection point in trucking where technology can finally have an impact," he has said. The hardware was always there. What changed is that the software can finally hold the entire board in its head at once, which is the only way to play a game with 20 quintillion moves.
The driver, not just the truck
Here's the twist that keeps the story from being just another efficiency play. Optimizing a truck for profit usually means squeezing the driver. Khoury insists on optimizing both at once: profit per truck and driver experience, in the same equation. Higher pay. Predictable weekly home time. No phone calls begging dispatch for the next load. The same algorithm that fattens margins is supposed to make the job livable, on the theory that a driver who stays is cheaper and better than a driver you keep rehiring.
aifleet, by the numbers
Self-reported performance vs. the industry baseline
Beirut to Berkeley to a freight desk in Austin.
Khoury did not grow up in trucking. He trained as a civil engineer at the American University of Beirut, finishing in 2003, then crossed an ocean for a master's in civil engineering at UC Berkeley. He started where engineers start, managing projects at Langan Engineering, before the gravity of strategy work pulled him in. An MBA from NYU Stern followed, then years at the management consultancy A.T. Kearney, climbing from associate to principal.
Consulting is where you learn to see a system's inefficiencies and itch to fix them. The itch eventually landed him inside the industry itself: Chief Strategy Officer at US Xpress, one of the country's larger trucking firms. From that seat he watched the model up close and concluded it was broken in a way that couldn't be patched from within. In 2020 he left to co-found aifleet and prove the point from scratch.
The believers
By 2024 the capital was catching up to the conviction. aifleet closed a $16.6 million Series B led by Heron Rock, with Volvo Group Venture Capital joining in, pushing total funding to roughly $55 million. Volvo builds the trucks; its venture arm backing a software-first carrier is the kind of vote that says the inflection point Khoury keeps describing might be real.
A driver should never have to call their dispatcher and say, 'I'm waiting for my next load.'
Six sentences that explain the whole company.
We are all in on truly disrupting the trucking industry with our unique AI technology.
It's a massively inefficient and fragmented market with half a million carriers.
Large fleets are hiring tens of thousands of drivers a year. It's a retention problem.
We're probably at this inflection point in trucking where technology can finally have an impact.
The things that make the file interesting.
aifleet's AI evaluates roughly 20 quintillion route combinations a week. The human brain taps out somewhere around three.
His contrarian thesis fits on a bumper sticker: there is no driver shortage, only a retention problem in disguise.
Trained as a civil engineer, he now designs systems made of trucks, drivers and code instead of concrete.
Volvo's venture capital arm backed him - a truck maker betting on a company that treats freight as software.
aifleet, in motion.
For a closer look at the model Khoury describes, aifleet's own walkthrough of its AI-driven approach is a useful primer: aifleet - What's Next in Auto | Mobility Tech (YouTube).