Logistics AI Automation Workflow Engineering
Case Study

Cargofy AI Automation.

Automated dispatch workflows that eliminated manual scheduling work and saved Cargofy's operations team 40+ hours every week.

40+ Hours saved weekly
70% Dispatch tasks automated
1 quarter To measurable ROI

The challenge

Cargofy's dispatch team was manually matching drivers to routes, cross-checking availability, and re-keying the same shipment data across multiple spreadsheets and tools every single day. As order volume grew, the manual process became a bottleneck that limited how many shipments the team could realistically handle.

What we did

We mapped the entire dispatch workflow end to end, then designed an AI-assisted automation layer that sat on top of Cargofy's existing systems rather than replacing them — reducing implementation risk and avoiding a disruptive platform migration.

  • Built an automated driver-to-route matching system based on availability, location and load type
  • Connected previously siloed spreadsheets and tools into one automated data flow
  • Added AI-assisted exception handling for edge cases that still need a human decision
  • Trained the operations team on the new workflow with a phased rollout

The result

The automation eliminated the majority of manual dispatch work, saving the operations team more than 40 hours per week collectively. Roughly 70% of what was previously manual scheduling is now handled automatically, freeing the team to focus on exceptions and customer-facing issues instead of repetitive data entry.

"Their AI automation work saved our operations team dozens of hours every week. The ROI was clear within the first quarter." David Kim, COO, Cargofy

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