How One AI Platform Is Removing Manual Work from Transportation Operations

Datatruck has released a major upgrade to its TruckGPT platform, offering a look at what embedded operational AI actually looks like in a high-friction industry. The platform targets transportation management systems (TMS), where manual data entry, slow communications, and dispatch inefficiencies cost carriers time and money every day.

The updated TruckGPT extracts and populates data from rate confirmations, bills of lading, and proofs of delivery in seconds — eliminating a step that has historically consumed hours of dispatcher time. A redesigned interface now highlights matched data fields and flags discrepancies before they reach accounting or factoring workflows.

"The freight market doesn't slow down for manual work," said CEO and co-founder Shah Rahmanov. "The carriers that win in this environment are the ones who've removed the friction from their operations."

What the Platform Actually Does

Beyond document processing, Datatruck's platform includes:

• AI Dispatcher — scans multiple load boards simultaneously and can automatically book freight
• AI Updater — manages broker and driver communications without requiring human intervention
• Analytics Tools — provide real-time insight into fleet performance and profitability

The company reports that carriers using the platform have booked freight up to 40% faster and reduced routine communication time by as much as 70%.

Key Takeaways

• The Datatruck model represents a shift from "add-on AI" to "AI-native" platforms — their core argument is that competitors still bolt AI onto legacy systems, while TruckGPT is built around it from the ground up
• Chief AI Officer Ulugbek Ergashev's framing applies well beyond trucking: "If it's repetitive, automate it. If it requires judgment, surface the right data to make that judgment faster and smarter"
• The 70% reduction in communication time demonstrates that AI's biggest ROI often comes not from complex tasks, but from eliminating the administrative overhead surrounding them

The lesson here is applicable to any operations-heavy business: the first step toward AI transformation is identifying where manual data entry and routine communication are quietly draining capacity.

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