CASE STUDY · LOGISTICS
How Vertex Freight cut deadhead miles by 32% with AI dispatch.
A mid-sized freight brokerage managing 400+ loads a week was losing margin to empty return trips. Echofied built an AI dispatch agent that monitors driver location and automatically matches them with backhaul loads.
32%
Reduction in deadhead miles
$142k
Added gross margin in Year 1
18 hrs
Dispatcher time saved per week
The Before & After
Before Echofied
- Dispatchers manually checking 3 different boards to find backhauls.
- Trucks driving 150+ miles empty after drop-offs.
- Drivers waiting 4+ hours for dispatch instructions via phone.
- Billing and invoicing handled 5 days after delivery.
After Echofied
- AI agent scans load boards and predicts optimal backhauls instantly.
- Automated SMS sent to driver with next load 2 hours before drop-off.
- Deadhead miles cut to under 20 miles per route.
- Invoice auto-generated and pushed to QuickBooks upon delivery scan.
The Technology Stack
| System | Role | How Echofied Connects |
|---|---|---|
| McLeod TMS | Load management & dispatch | API Integration (Read/Write). Agent pulls active loads, writes new assignments. |
| Samsara | Fleet tracking & ELD | API Webhook. Triggered when truck status changes to "Empty". |
| QuickBooks Online | Accounting & Invoicing | API Integration. Generates invoices instantly based on delivery confirmation. |
| Slack | Team communication | MCP Server. Alerts dispatchers of exceptions or approval requests. |
The Automation Workflow
- Trigger: Samsara sends a webhook that Truck #42 has dropped its load and is now empty.
- Action: Echofied agent queries McLeod TMS for available backhauls within a 50-mile radius.
- Match: Agent finds a load matching the driver's HOS (Hours of Service) and weight capacity.
- Approval: Agent sends a Slack message to the dispatcher: "Match found: Load #8821. Approve?"
- Execution: Dispatcher clicks "Approve". Agent writes the assignment to McLeod and sends an SMS to the driver with the new route.