What does a typical document flow in transport look like?
A trip starts with a trip order or load instruction, sometimes as a structured EDI message, but more often as a PDF in the inbox or an Excel attachment from the client. The planner converts that into an assignment in the TMS. Along the way, the driver signs a CMR waybill, sometimes digitally but in many cases still on paper. At delivery, a delivery note is added, signed by the recipient. Afterwards, the administrative team processes the incoming invoice from the subcontractor or sub-carrier and sends out the freight invoice. Every step in that chain produces a document. And every document comes in its own format, depending on who is on the other side.
Where does logistics document processing concretely break down?
The bottleneck is rarely one document, but the combination. Client A sends a trip order as a PDF with fixed fields; client B sends an Excel file with a different column layout; client C calls in the order and the planner types it in manually. The CMR the driver sends back is a photo on WhatsApp, a scan via an app, or a stack of paper that arrives weekly. The delivery note has a signature, but the reference number appears in a different position than the TMS expects. All that variation means someone repeatedly translates what comes in into what the system needs. At Cabooter Group, a logistics and transport company, this amounted to more than 70,000 documents per year being processed manually. After automating with dottle, 85 percent of those documents are processed fully automatically, representing a saving of approximately 110,000 euros per year.
When does automating logistics document flows pay off?
Automation pays off when volume is structurally high enough and the process is sufficiently defined. As a rule of thumb: if your team processes more than a few hundred similar documents per month, automation starts to become cost-effective. The process also needs to be recognisable: the same document types, the same fields you want to extract, the same destination in your TMS or accounting system. Does it not pay off? That is an equally valid answer. If you handle twenty trips per month for three regular clients who all consistently send the same format, manual processing is probably faster than setting up an automation flow. And if the source data is structurally poor, think unreadable scans or half-completed forms, even the best automation will struggle. Automation does not fix data quality problems; it accelerates what already works.
What does document AI do differently from standard OCR or scan-and-recognise?
Traditional scan-and-recognise software identifies text at a fixed position in a document. For that, you need to configure a template per client: field A is at coordinate X, field B is at coordinate Y. That works well when every client always sends the same format. In transport and logistics practice, that is rarely the case. Document AI reads the document context: it understands that a reference number is a reference number, even if one client puts it top-left and another puts it bottom-right, or if the column heading is worded differently. It delivers the extracted values into your TMS, ERP, or accounting system, including a flag when something is uncertain or when a value does not match what is already in the system. The employee approves; the reading work is already done.
How do you approach automating logistics document flows in practice?
Start with the document that causes the most pain. That is usually not the document with the highest volume, but the one that introduces the most errors or takes the longest to process. In transport, that is often the incoming trip order or the CMR after delivery. First, map out how many documents your team processes per month, through how many channels they arrive, and in how many formats. Then look at the system on the other end: what does your TMS or accounting system expect as input, and which fields are truly mandatory? That information determines what you need to extract and what you can match against. An implementation does not have to take months. dottle goes live in two weeks, with no setup fee, and charges tiered prices per document. That way you know what it costs before you roll it out.