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All case studies
AI
2026

AI-powered dispatch automation that saved 20+ hours a week

Built a workflow automation layer that reads incoming freight requests, matches drivers, and drafts dispatch confirmations automatically.

AI & Automation
Full-Stack Development

The problem

Ridgeline's ops team manually matched freight requests to available drivers and typed out confirmations by hand, a process that scaled poorly as request volume grew.

The solution

We built an automation pipeline using an LLM-assisted matching engine and n8n workflows that reads incoming requests, ranks driver matches against constraints, and drafts confirmations for one-click approval.

The result

The ops team now approves matches instead of building them from scratch, freeing over 20 hours a week that's been redirected to exception handling and customer relationships.

Results at a glance

Ops hours saved / week20+
Match turnaround time-71%
Dispatch errors-38%
ClientRidgeline Logistics

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