AI for logistics & transport, grounded in your own carrier contracts and compliance records.
AI for logistics & transport is grounded, auditable software RMAI builds on your own carrier contracts, PODs, and Chain of Responsibility records — so freight-invoice reconciliation, document data-entry, and the daily flood of “where is my order?” enquiries are extracted, matched, and drafted in minutes, with a dispatcher signing off every exception.
What actually slows a logistics and transport operation down.
The biggest constraints in transport are rarely the freight itself — they are operational: carrier invoices checked line by line, documents re-keyed before they become data, a front desk buried in status calls, and Chain of Responsibility records assembled only when an inspection forces it. Each one is a documents-and-data problem, which is exactly where grounded AI pays back.
Carrier invoices are reconciled line by line, or not at all
Most carrier invoices carry at least one error — a misapplied accessorial, the wrong fuel levy, a duplicated charge — and the errors tend to favour the carrier. Checking every line against the contracted rate card by hand does not scale, so overcharges get paid and disputes land late. Freight-audit studies put the leak at roughly 3–8% of total freight spend.
Documents are re-keyed before they become data
A single shipment can throw off seven to ten documents — bills of lading, PODs, packing lists, customs forms — arriving as PDFs and email attachments. Ops staff re-key them into the TMS by hand, losing up to half a day to transcription instead of moving freight.
"Where is my order?" swamps the front desk
Status enquiries — WISMO, the "where is my truck?" call — run between a quarter and half of inbound customer contact, and they spike at peak. With no self-serve visibility, dispatch answers the same question all day instead of clearing the exceptions that actually need a person.
Chain of Responsibility records are assembled after the fact
Driver fatigue hours, rest breaks, mass declarations, and maintenance records have to be audit-ready at any moment, with directors personally exposed. In most operations they sit scattered across driver logs, telematics, and email — pulled together only when an inspection forces it under the Heavy Vehicle National Law.
What changes once the back-office is grounded in your own contracts and records.
Operators working with RMAI recover back-office hours and protect margin at the same time. The outcomes below are illustrative of shipped patterns; every one keeps a person on the final call — nothing pays an invoice, closes a consignment, or finalises compliance on its own.
The questions leaders ask first.
The questions below are the ones RMAI hears in the first call — on safety, staffing, compliance, cost, and feasibility.
What the time recovered is worth.
Move the sliders for your own volumes; the benchmark shows where shipped builds have landed.
| Task | Before | After |
|---|---|---|
| Carrier invoice reconciliation | hours per carrier | < 2 min/invoice |
| POD / document data-entry | 2–4 hrs/day | exceptions only |
| "Where is my order?" enquiry | all to dispatch | 25–50% self-served |
| CoR evidence pack | assembled on demand | always audit-ready |
What RMAI has built for this sector.
The applications below are grounded, human-in-the-loop tools RMAI has built or scoped for this sector — illustrative of the patterns we ship.
Shipment-Status Responder
Reads inbound "where is my order?" enquiries, pulls the current milestone and ETA from your TMS and carrier feeds, and drafts a cited reply for a person to approve — escalating any delayed or unavailable shipment instead of inventing a time. It never sends on its own.
CoR-Evidence Monitor
Watches the driver logs, telematics, and maintenance records where Chain of Responsibility evidence lands, flags a fatigue, mass, or work-hour breach before an inspection finds it, and assembles an audit-ready evidence pack against the Heavy Vehicle National Law — surfacing exceptions for the compliance manager, never signing off on its own.
POD Reconciliation
Dramatised POD Reconciliation demo for logistics (fake data) — shows the pattern; a person approves each output.
Carrier-Invoice Reconciler
Extracts every line on a carrier invoice, matches it against the contracted rate card — fuel levies, zone pricing, weight breaks — and flags overcharges with a draft dispute attached, holding each exception for a person to clear. It never approves or pays an invoice on its own.
Weighbridge-to-Ledger Reconciler
Reads weighbridge dockets, matches each against the grower contract, and drafts the invoice in Xero or MYOB — flagging missing tares, over-GVM loads, and price mismatches for a person to clear.
Prompts you can use today, for free.
Sector-specific prompts RMAI uses as starting points. Copy one, run it against your own documents in any assistant, and see the shape of the answer before you talk to us.
How RMAI would work with you.
Every engagement starts with the diagnostic and scales from there. These link through to how RMAI works.
What a defensible result looks like.
These are published third-party results from comparable Australian operators — illustrative of the target RMAI builds toward, with a human in the loop throughout. They are not RMAI client claims.
Considering AI for your logistics and transport operation?
The two-week diagnostic is the right place to start. Fixed scope, fixed price. We’ll tell you whether the pattern fits and what the build would look like.