AI systems for logistics and operations teams
Freight runs on documents. Invoices, PODs, CMRs, packing lists, commercial invoices — arriving as PDFs, scans, EDI feeds and photographs taken on a driver's phone in a lorry park. Somebody opens each one, keys it in, matches it to a job, and queries the difference. That's the work we automate.
The work that eats the week
Every logistics business we've worked in has the same four bottlenecks. None of them are the actual job of moving freight.
Invoices arriving in every format known to man
Carrier invoices, supplier invoices, self-bills. PDF, scanned image, emailed photo, portal download. Each one gets opened, read, keyed into the finance system, matched to a job number, and queried if it doesn't tie. The work is identical every time and it never stops.
This is the exact workflow we cut from 4 hours to 20 minutes per person, per weekCarrier invoice lines nobody has time to audit
Fuel surcharges, DIM re-rates, residential surcharges, redelivery fees, demurrage, detention, accessorials. Auditing a £9 re-rate costs more in admin time than the £9 you'd recover, so most operators never audit at all — which is precisely why the re-rates keep arriving.
“Where's my POD?”
A driver delivers, photographs a signature, and moves on. The POD doesn't reach the customer, so the customer withholds payment, so credit control chases, so operations has to go and find a scan from three weeks ago. It's the logistics version of “where is my order”, and it delays cash.
Customs data that lives in someone else's inbox
The declaration itself isn't the burden. The burden is extracting a correct commodity code, weight, value and origin out of a customer who sent a one-line email — and then chasing them while a container accrues demurrage at the port.
What we'd build for a logistics operation
Each of these is a single, defined job. We build one, prove it, then look at the next — rather than selling you a platform and hoping you adopt it.
Invoice-to-system worker
Reads any inbound document format, extracts header and line data, matches it to the consignment or purchase order, posts the clean ones, and queues only the exceptions for a person to look at.
Our proven build. Typical setup 3–4 weeks.Carrier invoice audit
Re-rates every invoice line against your contracted rate card and the service actually delivered. Flags duplicate charges, invalid accessorials and surcharge errors, then drafts the dispute email with the evidence attached.
Makes small disputes economically worth raising.POD retrieval and distribution
Matches driver-captured images to consignments, reads the signature block, files it against the job, and pushes it to the customer automatically — before they ask.
Removes an entire category of inbound email.Exception triage
Watches carrier tracking events, flags consignments at risk of missing their window, and drafts the customer notification before the customer notices. Turns a complaint into a courtesy call.
Customs data completeness
Checks a customer's documents against the fields a declaration actually needs, then drafts the chase for what's missing. It prepares and evidences; a customs-competent person files.
Drafts only — see the limits below.Quote and tender drafting
Parses a lane spreadsheet, prices it against your rate cards, and produces a formatted response for the commercial team to check and send. Turnaround speed moves win rates.
The regulatory bits that actually constrain the build
Logistics is less heavily regulated than healthcare or financial services, but the rules that do apply carry criminal liability rather than a fine. That changes where a human has to sit in the process.
- <strong>Customs declarations.</strong> Legal liability for commodity classification, valuation and origin sits with the declarant — not with a software vendor. Our systems prepare and evidence declarations. A customs-competent person files them.
- <strong>Drivers' hours and tachograph rules.</strong> Criminal liability, and the safety consequence is people dying. A system can surface remaining drive time. A planner decides whether the drop happens.
- <strong>Dangerous goods.</strong> ADR classification is attributed to a named DGSA. We don't automate it.
- <strong>Sanctions and denied-party screening.</strong> This needs deterministic matching against official lists with human adjudication of hits — not a probabilistic model. We build the screening as a hard check, not an inference.
- <strong>Telematics and driver data.</strong> Vehicle cameras, tacho data and tracking are employee monitoring under UK GDPR. They need a lawful basis and a Data Protection Impact Assessment. This is the most commonly missed requirement in the sector.
A 120-staff logistics firm with a 12-person accounting team. Weekly invoice processing, per person. The pattern is the one that repeats across every build we do: the time didn't come from replacing anyone — it came from removing the waiting and the re-keying between steps.
What we won't automate in a logistics business
These aren't hedges. They're the things we'd refuse to build, and the reasons why.
Filing customs declarations autonomously
A model confidently producing an eight-digit commodity code is a duty liability and an HMRC audit waiting to happen. It drafts; a person with the competence and the legal exposure signs.
Deciding whether a driver can do one more drop
Drivers' hours are a criminal matter and a safety one. The system shows the planner what's left. The planner decides.
Issuing credit notes or accepting claims
Financial concessions need a person who can be held to the decision. The system assembles the claim file — POD, photographs, temperature logs, correspondence — and hands it over complete.
Notifying customers of serious failures
A temperature excursion on a pharma load, a lost high-value consignment, an injury. Those calls are made by a human being, immediately, and no system should sit between you and that conversation.
Common questions.
Can AI process freight invoices accurately?
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Yes, for extraction and matching — with an exception queue. A well-built system reads the document, pulls the line data, and matches it to the consignment or purchase order. Where it's confident and the numbers tie, it posts. Where anything doesn't reconcile, it stops and queues the item for a person. The accuracy that matters isn't “how often is it right”; it's “how reliably does it know when it isn't”. Unsupervised posting of every invoice is not something we'd build.
Can AI complete customs declarations?
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No — and be wary of anyone who says otherwise. Legal liability for the accuracy of commodity classification, customs valuation and preferential origin sits with the declarant. A system can gather the data, check it for completeness, chase the customer for what's missing and prepare the declaration with its reasoning evidenced. Filing it is a human decision by someone competent to make it.
How does an AI system connect to a TMS or WMS?
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Through whatever interface your systems already expose — API, database, EDI, or scheduled file exchange. We build around your existing stack rather than asking you to replace it. In practice most logistics builds read from email and shared folders on the way in, and write into the TMS or finance system on the way out, so the people using it never open anything new.
What happens when the system gets it wrong at 2am?
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It stops and escalates, rather than guessing. Every system we build for a 24/7 operation has an explicit confidence threshold and a defined escalation path: what it does when it isn't sure, who it tells, and what it never attempts alone. Designing that path is most of the work in a logistics build — the happy path is the easy part.
How long does a logistics AI build take?
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Typically 4–8 weeks from signed scope to live, for one workflow. Invoice processing is usually at the shorter end because the inputs and outputs are well defined. Anything touching customs or planning takes longer, because the escalation design needs more care. We agree the fee before we start and don't bill hourly.
Start with the documents.
If your team is re-keying data that already exists somewhere else, that's the place to begin. Tell us what the work is and we'll tell you honestly whether it's worth automating.