Exceptions are the job. Copy-paste isn’t.
Shipments fail in messy, human ways — wrong addresses, missing paperwork, customs holds. AI agents read, classify, and resolve the routine exceptions while your people keep the judgment calls and the customer relationships.
A logistics operations team lives between three systems and an inbox. Every exception means reading an email, pulling context from the TMS, pasting between screens, and hoping nothing slips — and management knows the team is at capacity but can’t quantify where the hours actually go, let alone what automating them would be worth.
That is where we start: a two-week audit that instruments the real work, then production AI workflows for the top of the ranked list. Agents handle the volume with confidence thresholds and a full audit trail; humans handle the exceptions to the exceptions. You get a dashboard that shows, in hours, what moved from manual to automated.
What we would do at logistics
Agents read incoming exception emails, classify them, pull context from the TMS, and draft resolutions. High-confidence cases execute automatically; everything else queues for a person with the context pre-assembled. The reports that used to take days of manual assembly generate themselves from the workflow’s audit trail.
The portals and integrations around the operation
Explore Software Development →Customer tracking portals, status APIs, document pipelines, integrations between your TMS, ERP, and the carriers and customs systems around them — anything with an API, and we build one where none exists. Built and shipped the same way as everything we make: weeks, production deploys from week one, code you own.
The operators closest to the work learn to supervise, monitor, and extend the workflows — using your exceptions, your systems, and your reporting as the curriculum. Each participant ships a real improvement during the program and leaves with playbooks, so the automations don’t become a black box owned by outsiders.
900 hours a month back at a mid-market operator
A twelve-person operations team was handling every shipment exception by hand — emails, three systems, and a lot of copy-paste. Our two-week audit found three workflows consuming 70% of the team’s time; none of them had been nominated as a problem by anyone.
Eleven days later the first workflow was live; within ten weeks all three were. 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, and 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.”
Questions logistics ask us
Which systems can you integrate with?
+
Anything with an API: TMS, ERP, EDI feeds, ticketing, email, spreadsheets, document stores, and carrier or customs systems that expose one. Where no API exists, we build one. Your stack stays; the copy-paste goes.
What happens when the AI gets an exception wrong?
+
Every workflow carries confidence thresholds and human checkpoints. Low-risk steps run automatically; anything high-stakes or ambiguous routes to a person — with the context already assembled, so approval takes seconds. Every automated action is logged and auditable, and error rates are on the savings dashboard, not buried.
Does this replace members of the ops team?
+
Almost never, in practice. The work we automate is the part your team already resents. The usual outcome is the same people doing higher-value work — the case study team refocused on the complex exceptions and on customers, and liked their jobs more.
Find your 900 hours
The audit comes first: two weeks shadowing and instrumenting your team, ending with the map of where the hours go and what automating them is worth. Even if you never automate a thing, the map changes how you run the team — it did for them.