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.
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
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