Case Study — Mid-market logistics operator

Reclaiming 900 hours a month from manual operations

A twelve-person operations team was drowning in manual exception handling and copy-paste reporting. We automated the top three workflows and gave them 900 hours a month back.

900 hrs
returned per month
-80%
processing error rate
11 days
to first workflow live

The challenge

Industry: Logistics

Service: AI Workflow Automation

Duration: 10 weeks

Shipments fail in messy, human ways: wrong addresses, missing paperwork, customs holds. A team of twelve handled every exception by hand — emails, three systems, and a lot of copy-paste between them.

Management knew the team was at capacity but could not quantify where the hours went, let alone what automation would be worth.

The approach

01

Two-week audit before a single automation

We shadowed the team and instrumented their tools. The data showed three workflows consuming 70% of the team's time — none of which anyone had nominated as a problem.

02

Exceptions routed to agents, judgment routed to people

AI agents now read incoming exception emails, classify them, pull context from the TMS, and draft resolutions. High-confidence cases execute automatically; everything else queues for human approval with the context pre-assembled.

03

Reporting built as a by-product

The management reports that used to take two days a month of manual assembly now generate themselves from the workflow's audit trail.

The outcome

Within ten weeks all three workflows were live. The team refocused on the complex cases that actually need human judgment — and on customers instead of keyboards.

The savings dashboard shows 900+ automated hours per month and an 80% reduction in processing errors. The client has since commissioned a second phase for their finance back office.

The audit alone changed how we run the team. Seeing where the hours actually went was worth the project, and the automations were the bonus.

Head of Operations, Mid-market logistics operator

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