Datatruck is selling an AI-native transportation management system to fleets as small as five trucks, betting it can carry them to 25 trucks without the million-dollar enterprise software bill that growth historically demanded. The company just landed a spot on the FreightWaves Freight Tech 100 and is now in the running for the Freight Tech Top 25, with winners announced at the F3 conference.

Head of Product Jordan Kidd calls the small and mid-size fleet segment "an overlooked space," one that legacy vendors have largely left stranded between stripped-down free tools and platforms costing millions per year to buy and operate. AI-assisted development is compressing that gap, making one platform viable across a broader slice of the market. Growth from five trucks to 25, Kidd argues, "wouldn't have been possible before" on affordable software.

Why can't small carriers keep running on spreadsheets?

Because their trading partners won't let them. Kidd said shippers' real-time tracking mandates and tighter integration requirements from invoice factoring companies are forcing formal software adoption whether operators want it or not.

"It's becoming a requirement to have tracking, real-time tracking," Kidd said. "There's just so many parts of the operation that are basically enforcing a requirement for some sort of software."

Email, spreadsheets and QuickBooks no longer cut it, even for the smallest carriers. That's a commercial squeeze: adopt software, or lose loads.

What changed with the 2017 ELD mandate?

Kidd pointed to the 2017 electronic logging device mandate as a structural inflection point the TMS industry has largely failed to address in nearly ten years. Before the mandate, a TMS was essentially a digital clipboard — loads, invoices, driver pay. After it, asset location data began flowing into systems automatically, and the architecture problem changed entirely.

Most providers, Kidd said, never reinvented their core paradigm to match the new data flows. His verdict on incumbents bolting AI onto aging stacks: "I think it's difficult to take an infrastructure that's 20 or 30 years old and bolt on AI and really see the value that you need to see out of an AI investment."

He's equally skeptical of point-solution AI add-ons — AI billers, AI callers and similar tools — that attach to existing systems without a shared data layer, creating integration friction that erodes their individual value.

What does the carrier moat look like now?

Large carriers' software advantage is eroding, in Kidd's framing. "Some of the moat that the large carriers had was systems to undergird customer requirements, driver requirements, just all of the parts of the operation," he said. "They could run really well on these large established systems. But as we see technology and TMS progressing, that technology is being democratized down to the smaller carriers."

Datatruck's pitch centers on being both a system of record and a system of action, with end-to-end cohesion across dispatching, billing and asset visibility. Kidd framed the payoff in concrete margin terms: loads that fall through the cracks when billing responsibility sits across multiple staff members are exactly the leak software can close once a carrier outgrows the point where one person holds all operational context in their head.

For small carriers, the pitch is scale without overhead. For incumbents, it's a warning that AI-native architecture — not bolted-on features — is the competitive front. If Kidd's read on the ELD-driven data shift is right, the next wave of TMS consolidation will favor platforms built after 2017, not retrofitted for it. The Freight Tech Top 25 vote at F3 will offer an early market check.