Dispatch time cut 68%

Cut dispatch decision time 68% by matching loads to drivers automatically.

Industry Logistics / Trucking
Region United States
Client size Regional carrier, 200+ trucks
Delivered in 11 weeks

Inside the rollout

Meridian Fleet Services runs over 200 trucks across the Texas Triangle, and every load still had to be matched to a driver by a small dispatch team working the phones and a spreadsheet. Matching the right driver to the right load, factoring in hours-of-service limits, deadhead miles and equipment type, ate most of a dispatcher's shift, and a bad match could mean a driver running out of hours mid-route or a load sitting uncovered overnight.

Our approach

Meridian wanted an agent that could sit over their existing TMS and propose a ranked shortlist of drivers for every new load the moment it came in, factoring in the same constraints a senior dispatcher would, while leaving the final call with a human. We scoped narrow: one region, one equipment type, then expanded once dispatchers trusted the shortlist.

Results at a glance

We went from dispatchers eyeballing a board to getting a ranked list the second a load drops. They still make the call, but they are not starting from zero every time. Deadhead miles are down and nobody is scrambling to cover a load at 6pm anymore.
Meridian Fleet Services are an example of a business finding real margin in a problem everyone assumed was just the cost of scale. Cutting dispatch time by more than two thirds across a 200-truck fleet is not a small operational win, it changes what dispatchers spend their day doing. The presentation to the panel made clear this was a team effort between dispatch and drivers, not something imposed from outside. That buy-in is a large part of why the system stuck rather than being quietly abandoned after launch. What the panel had to say about Meridian Fleet Services

AI is here. Most will react. The few with a plan will lead.

We build for those few.

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