An implementation partner can build AI that reads bills of lading, commercial invoices and customs paperwork, extracts the fields into your transport management system or ERP, sorts the shipping inbox and drafts status replies. A person checks each extraction and each reply before it is saved or sent, and exceptions are flagged instead of guessed.
#Key takeaways
- The work to automate is reading documents, re-keying fields and answering status emails, not running the shipment.
- Document extraction needs a human check, because one wrong container number or HS code becomes a customs problem.
- Email triage and status replies work when AI can look up the shipment record in your own systems.
- Exceptions, such as missing documents or mismatched weights, are flagged to a person, never resolved silently.
- Pick a builder who shows a workflow running in production, not a demo.
#What can AI do with shipping documents?
AI reads the document, whether it arrives as a PDF, a scan or an email attachment, and pulls out the fields your team types today: shipper, consignee, container numbers, ports, weights, HS codes, invoice lines and incoterms. It then places them into a draft record in your transport management system or ERP.
- bills of lading. parties, container and seal numbers, ports of loading and discharge, package counts and weights.
- commercial invoices and packing lists. line items, quantities, HS codes and country of origin, compared against each other.
- customs paperwork. declaration references and the supporting documents a broker asks for, checked for gaps before submission.
This is the same problem as re-keying between systems, covered in AI for data entry. The difference in logistics is that one document feeds several parties, so a wrong field travels.
#Why does extraction need a human check?
Because extraction accuracy is uneven across document layouts. A clean carrier PDF reads well; a faxed, stamped or handwritten packing list does not. A person reviews each extraction, with low-confidence fields highlighted, before the record is saved. Their corrections show where the workflow needs work.
Illustrative example, the numbers are assumptions: a freight forwarder handling 600 shipment files in a typical week, each with four or five documents. If most extractions need only a glance and a minority need correction, the operations team moves from typing every field to checking the ones flagged.
#How does AI handle the shipping inbox?
AI reads each incoming email, identifies the shipment reference and the request, and sorts it: status question, document submission, booking change, complaint or exception. For status questions, it looks up the shipment record in your systems and drafts a reply. The customer service agent edits and sends.
Email carries a specific risk: a message can contain instructions written to manipulate the AI. The OWASP top 10 for LLM applications lists prompt injection as the first risk, which is why replies stay drafts and AI cannot change a booking on its own.
#What counts as an exception, and who sees it?
An exception is anything that does not match: a weight on the bill of lading that differs from the packing list, a missing certificate of origin, a consignee name that does not match the booking. AI flags it with the documents side by side and routes it to the person who resolves it today, usually the operations coordinator or the customs lead.
This is a workflow, not an autonomous agent. Anthropic, december 2024 describes workflows as predefined code paths and advises starting with the simplest approach that works. In logistics, predictable beats clever.
We are
Stennir builds one document or email workflow into your transport management system, ERP and inbox, with a person checking every extraction and reply, and hands you the off switch.
We aren't
Stennir is not an OCR product you rent, and not an agent that books or clears shipments on its own.
#Who can build AI document processing for a logistics company?
The options are a document processing product, an RPA vendor, or an implementation partner. Products handle common layouts well; a partner maps your actual documents, systems and exceptions and stays accountable once it runs. Gartner, june 2025 warned of "agent washing", so ask for production experience, not demos.
AI implementation at Stennir means one workflow running with real users, in Arabic and English, hosted where your rules require, then managed AI operations with a named owner. You pay for finished work.
#What should a logistics operations lead do next?
Pick the document type or inbox that takes the most typing, collect a sample of real files including the messy ones, and name the person who would check the output. See AI for operations, take the free readiness assessment or book a 30-minute call.
#Common questions
What do you need from us?
A sample of real documents and emails, including scans and the awkward layouts, read access to your transport management system or ERP, and the person who checks the output today. Stennir maps the steps with them, writes down the fields and the rules, and agrees which exceptions must always go to a person.
Does it read Arabic documents?
Yes. Arabic and English are fully supported, including bilingual invoices and customs paperwork. Stennir tests extraction on your own documents, field by field, before anything runs, because stamps, scan quality and mixed scripts vary by carrier and port. Other languages are available on request and tested the same way.
Where does shipment data stay?
In the region your rules require. Stennir hosts the workflow and runs inference where your data protection obligations and customer contracts point. You own the accounts, the data and the off switch, every action is logged, and documents are kept only as long as the workflow and your retention policy need them.
What could go wrong?
A wrong container number or HS code saved without review, a status reply that quotes an outdated arrival, or an exception that is missed. That is why every extraction is checked by a person, low-confidence fields are highlighted, replies stay drafts until sent, and mismatches are flagged rather than resolved by the AI.
