Software for logistics operators, built around exceptions.

The cost centre in a transport operation is exceptions: the failed delivery, the missing paperwork, the vehicle off the road. Each one generates calls, rework and a customer forming an opinion.

Most systems record what happened. Far fewer act on it fast enough to change the outcome.

Knowing the failure rate tells you little. Knowing that a third of failures come from one depot on one day of the week tells you what to change. Most operations have this data and no way to see it.

Exception handling and customer notification as a first build sits in the middle of the £8,000 to £30,000 range, because it usually touches more than one existing system. Document reading for delivery notes and proof of delivery is custom AI work at £8,000 to £25,000.

Where a pilot already exists and cannot reach production, implementation at £4,000 to £15,000 is the relevant service rather than a fresh build.

Exceptions per hundred jobs, and staff minutes spent per exception. That second number is the one nobody records and the one that carries the cost, because it is absorbed by experienced people on the phone.

Then proportion of customers who are told about a problem before they ask. That single line drives most of the complaint volume in this sector and it is entirely within your control.

A 30-minute call to hear how the operation runs today, then a paid discovery step: interviews with the people doing the work, a look at the systems and data you already hold, and a ranked list of what would pay back, each with a price, a timeline and the monthly running cost once live. In most logistics or transport operator engagements the first thing built is document intake for proof of delivery and invoicing, so cash comes in when the job is done rather than when the paperwork catches up, because it is measurable inside a month and it funds the rest.

The build runs in weekly demos against your real inputs, including the messy ones. Integration with the systems you already run comes before anything clever, because that is where most of the value and most of the risk sits. Go-live is followed by handover: the code, the provider accounts and the credentials in your name, a runbook, documentation and a recorded walkthrough, plus a session for the people who will use it daily. Every price is fixed in writing before work starts, with a list of what is not included.

Operator licensing, driver hours and tachograph rules, vehicle maintenance records and, for international work, customs documentation all produce records that must be complete and retrievable. Software cannot hold the licence, but it can make sure the defect report is filed, the inspection is booked before the due date, the driver’s hours are visible before the next job is allocated and the customs paperwork is assembled from the consignment rather than retyped. Customer and driver data carry the ordinary UK GDPR duties.

Our published prices apply to every sector: an AI adoption audit at £2,500 to £6,000 fixed, credited in full against any build; a first AI implementation at £4,000 to £15,000; a custom AI system at £8,000 to £25,000; applications at £8,000 to £30,000 per phase; websites at £4,000 to £16,000; training from £1,200. For a operator that usually means proof-of-delivery and invoicing automation as the first implementation, then customer-facing tracking and enquiry answering as a custom system, with the transport management system you already run kept as the record.

The running cost is stated before go-live, per feature, and it scales with volume rather than headcount. From operating our own AI products, the model is rarely the expensive part; the channels around it, telephony and messaging, usually are, and a well-designed workflow sends most of its work to the small, cheap models. Every system we build reports cost per feature from day one and has spending ceilings that were tested by watching them fire.

The gap between delivery and invoice is where an operator’s cash goes. Proof-of-delivery documents read into structured records the moment they arrive, matched to the job and pushed to the invoice, close it. The phone is the second cost: customers ringing to ask where their consignment is, answered by someone who has to look it up. An AI that answers with the live status and books collections lets the office deal with exceptions. The third is the exception itself: a late load, a failed delivery, a damaged consignment, where a system that flags it early is worth more than one that reports it later.