Logistics & transport

AI for the paperwork that moves the freight, without it leaving your perimeter.

The same lorry brings the delivery note by email, the CMR on paper and the packing list over WhatsApp, in five languages, and someone keys the references in by hand. Inferana reads that paperwork inside your perimeter, on a flat rate.

The rules that apply to you, point by point

What each regulation in your sector requires, and which part of that the deployment solves.

eFTI

Regulation (EU) 2020/1056
What it requires

Authorities must accept freight transport information in electronic form, with format and access requirements.

How we solve it

Delivery notes and CMRs extracted into structured fields inside your perimeter, with a record of every query.

Union Customs Code

Regulation (EU) 952/2013
What it requires

Accurate declarations, correct tariff classification and retention of supporting documents for the legal period.

How we solve it

Search across your past files to prepare and cross-check declarations, with every proposal reviewed by a person.

NIS2

Directive (EU) 2022/2555
What it requires

Transport is an essential sector: risk management, supply chain security and incident reporting.

How we solve it

Dedicated EU or on-premise deployment, with access control per team and deployment documentation for your risk analysis.

GDPR

Regulation (EU) 2016/679
What it requires

Legal basis and minimisation when handling driver, tachograph and fleet geolocation data.

How we solve it

Prompts and responses are never stored or used to train models, and inference stays where you deploy it.

Your most common use cases

The same ones you already use, specific to your sector.

See all use cases

Every shipment leaves a paper trail in five languages.
And someone keys it in by hand.

The freight moves on its own. The paperwork is moved by people, by hand, against the clock and on thin margins. This is what you hear on the traffic desk every day:

What happens today

The delivery note reaches me by email, over WhatsApp and on paper, in five languages.

Traffic desk administration

I have two people keying references out of a PDF all morning.

Administration lead

Two people are retiring and their tariff classification judgement goes with them.

Customs lead

We answer the incident after the customer has called three times.

B2B customer service

The haulier invoice does not match the delivery note and we find out when paying.

Finance

One week to answer a tender with four hundred lanes in it.

Commercial

On low double-digit margins I cannot pay per document.

Managing director

With Inferana

One extraction flow for email, WhatsApp and the scanner, running inside your perimeter.
References come off the document as structured fields and reach the TMS without passing through a keyboard.
The judgement in your past files stays searchable, and every proposed tariff heading is reviewed by a person against the source.
Incidents arrive sorted and ranked by urgency, with the delivery note and the proof of delivery already linked.
Every invoice is checked line by line against the delivery note, and the gaps show up before payment goes out.
The tender pack is summarised the same day: lanes, deadlines, penalties and what changed since last year.
Flat rate tied to capacity: processing a whole month of volume costs the same as processing half of it.

Sector FAQs

Wherever you decide: on European infrastructure we manage, or on-premise on your own infrastructure. In both cases prompts and responses are never stored or used to train models.

The rate is flat and tied to the capacity you deploy. A peak of two million delivery notes in one month costs the same as half a million, as long as the capacity holds. To size it we need your monthly volume, the document types and the response time you can live with.

It depends on the document. Open models read poor scans reasonably well, and there are cases where they fail: carbon copies, stamps over amounts, backlit phone photos. We will not quote an accuracy figure before seeing them. We run a sample of your real documents and measure accuracy per document type before anything is signed.

As support, with human review. It is useful to retrieve how something similar was classified in past files and to draft the entry. Responsibility for the declared heading stays with the declarant, and the system keeps a record of what was consulted to reach it.

With an on-premise deployment, their shipment paperwork stays in your infrastructure and the flow never leaves your network. You can show them the deployment diagram, the policy of not storing prompts or responses, and the access log per user and team.

No. The API is OpenAI-compatible: you integrate from what you already run by swapping the key and the endpoint. Your management systems remain the source of truth and receive the fields already extracted.

Yes, with the same key. There the query does go out to the model provider, so paperwork covered by customer confidentiality clauses is handled with the open models inside your perimeter. It is configured per team.

Yes, through the same flow as the scanner. A phone photo reads worse than a native PDF, especially backlit or with a stamp over the amount, and that gets measured before anything is signed using a sample of your real documents. Whatever does not read cleanly is flagged for review before it reaches the TMS.

The models are open and the API is OpenAI-compatible: you can take the weights with you and point the code elsewhere by changing a key. Your documents, your indexes and the extracted fields are exportable.

Tell us what you want to deploy and we will show you where Inferana fits.

In the demo we go through your case: which models you need, where they run and what it takes to meet the regulation that applies to you.

We reply within one business day.