WEX Teams With Euclid to Bring Agentic AI to Trucking

WEX

Payments solutions provider WEX teamed with Euclid AI, a provider of agentic artificial intelligence solutions for the trucking industry, according to a Tuesday (Oct 27) press release.

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    The collaboration is designed to bring AI agents to WEX’s over-the-road (OTR) customers to help them save time and money, the release said.

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    “Our customers are looking for practical ways to take cost and complexity out of running a fleet, and AI agents built specifically for trucking are a significant step forward,” Tim Hampton, senior vice president and general manager for the WEX OTR business, said in the release. “Euclid AI builds agents for operations where carriers need it the most. This important collaboration extends how WEX supports carriers beyond our own products.”

    AI is a “business imperative” for fleet operators, according to the release. The technology helps streamline compliance, paperwork processing, and keeping drivers and customers informed.

    Euclid’s AI agents have allowed fleet managers to handle five to 10 times more work and have reduced cost per transaction by 80% to 90%, letting carriers scale without adding costs, the release said.

    “We’ve already delivered major results for the largest carriers in the country,” Euclid AI CEO Ahmad Kakar said in the release. “Together, we’re putting that same power in the hands of WEX OTR customers, and we’ll keep building on this collaboration to serve them even better over time.”

    AI can help the trucking industry reduce the cost of breakdowns, PYMNTS reported May 19. Industrywide, such events lead to more than $25 billion annually in lost productivity. A single roadside breakdown can cost between $450 and $760 in direct repairs, not including the price of towing, rental replacements and missed revenue.

    “AI changes the model,” the report said. “Machine learning systems ingest real-time sensor readings alongside historical repair records, then identify the combinations of signals that tend to precede specific failures, often weeks before a breakdown occurs. The output isn’t raw data but a specific recommendation, such as a particular vehicle, a particular component or a service window that fits the route schedule. Repairs shift from roadside emergencies to planned shop visits.”