Intake & Extraction
AI Document Extraction for Logistics
Shipping paperwork read automatically, references, parties, quantities and dates written into your TMS, with doubtful fields held for a person.
Shipping paperwork never stops: delivery notes, bills of lading and proof-of-delivery scans, each from a different carrier in a different layout. This build reads them for content, pulls out references, parties, quantities, weights and dates with a confidence score on each field, and writes clean results to your TMS. Unsigned PODs and doubtful values wait for a person.
- Shipping documents read into your TMS without retyping
- Unsigned or incomplete PODs held as exceptions for review
- New carrier layouts handled without building new templates
$5,400
20–30 working days
Optional maintenance $270/mo
What it is
AI Document Extraction for Logistics reads the shipping paperwork that arrives in your inbox or upload folder, such as delivery notes, bills of lading or proof-of-delivery scans, and pulls out the fields you define with a confidence score on each. Clean results go to your TMS; doubtful ones wait for review.
Why businesses buy it
Every bill of lading or POD keyed by hand costs time, and every typo costs more: a wrong reference delays billing, and a missing signature turns into a disputed delivery weeks later. As volume grows, operations teams hire just to keep up with paperwork. This build reads the documents as they arrive and only asks a person about the doubtful ones, so your team handles exceptions instead of data entry. The written scope fixes the document types, fields and systems before you order.
Problems this solves
Proof-of-delivery scans pile up waiting for someone to key them
The system reads POD scans from your inbox or upload folder. It pulls out the consignee, delivery date and reference fields you define. Clean results post to your TMS, so billing is not held up.
Bill of lading details are retyped and errors reach invoices
Shipper, consignee, weights and piece counts come out of each bill of lading with a confidence score. Logistics validation rules check them before anything is written to your TMS.
Smudged or handwritten delivery notes slow the whole back office
Doubtful values wait in a review queue instead of being guessed. Your team checks only the uncertain fields, while legible paperwork flows straight through to the TMS.
A good fit if
Someone on your team retypes shipment references, consignee details and piece counts from PDFs into your TMS every day.
Customers ask where their paperwork is, and the answer depends on whether that document has been keyed in yet.
Most of your volume comes from up to three document types, even if each carrier lays them out differently.
You want missing signatures, unreadable dates or mismatched quantities flagged to a person instead of saved silently.
Not the right fit if
Your real problem is customers asking for shipment updates. See AI Order Tracking Agent, which sends accurate shipping updates proactively.
You are processing carrier or supplier invoices that need line-item checks and coding. See AI Invoice Intelligence for Logistics.
Documents arrive unsorted, in many types, through one inbox. Put AI Document Classification, in front of this build to sort them first.
You want extraction, order tracking, complaint handling and an operations assistant together. The AI Logistics Ops Stack, includes the core AI Document Extraction with those three.
How it works
- Paperwork arrives through one route. Delivery notes, bills of lading or POD scans land in the shared inbox or upload folder you choose, as attachments or files.
- Each document is read for content, not position. A shipment reference is found whether a carrier prints it in the header, a table or a stamp, so new layouts do not need a new template.
- Your fields come out with a confidence score. Up to 25 fields per document type, such as reference, shipper, consignee, pieces, weight, dates and signature present, each scored.
- Validation rules catch exceptions. A POD without a signature, a missing delivery date or a quantity that fails your rules is held as an exception instead of being written as complete.
- Clean results go straight to the destination. High-confidence fields are written into your TMS or tracking system, or a sheet if that is your record, linked to the source file.
- Doubtful fields wait for a person. Your named reviewer checks them in a queue, corrects where needed, and only then do they reach the system of record.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- At least 20 real samples of each document type, such as delivery notes, bills of lading or POD scans, redacted if you prefer.
- The fields to extract from each type, and the rules that make a document an exception.
- Access to the inbox or folder where paperwork arrives.
- Access to your TMS, tracking system or the destination sheet the fields should be written to.
- The person who reviews low-confidence fields and exceptions.
- Admin access and API keys for both connected systems, never sent by email.
- One decision-maker who approves the field list and signs off at launch.
- An API key for your own AI model account (for example OpenAI or Google Gemini), created for this build with a spending limit.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake verified, sample paperwork and field list confirmed.
Weeks 1–2
Extraction and exception rules built from the Logistics template.
Week 3
Inbox or folder and TMS connected, review queue configured.
Weeks 3–4
100 sample documents processed, accuracy report by field shared.
Week 4
Your review and two rounds of changes.
Go-live
Live on incoming paperwork, recorded handoff, support starts.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $5,400 |
| Express | 15–25 working days | $6,200 |
| Rush | 10–20 working days | $7,000 |
What you receive at handover
- AI Document Extraction for Logistics configured on one intake route and connected to your TMS or other agreed system
- Logistics field sets and validation rules for up to three document types, such as delivery notes, bills of lading and PODs
- A human review queue for low-confidence fields
- A test report using logistics scenarios, from 100 sample documents with an accuracy report
- An admin guide and a recorded 60-minute handoff session
- 30 days of post-launch support
Expected benefits and how to measure them
- Can shorten the wait between a delivery and the invoice going out.
- Helps cut billing queries caused by mistyped weights or references.
- Lets office staff spend less time keying paperwork in busy weeks.
- Time from delivery to POD recorded
- Compare delivery dates with the date the POD lands in your TMS. Use the month before launch and the month after.
- Invoice queries caused by document errors
- Tag disputed invoices by cause in your billing system and compare quarter on quarter.
- Documents processed per clerk per day
- Count from the intake log and review queue after launch. Compare with a manual count beforehand.
Before you start: Count PODs and bills of lading received per week and time how long each takes to key. Note invoice queries from paperwork errors last quarter.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build is one fixed price. Running costs are roughly $30 to $200 a month in your own accounts for OCR and AI usage plus storage, and they follow page volume: a depot processing a few hundred pages a month sits at the low end, a busy hub higher.
AI usage during build and testing is billed to your accounts too, so every provider relationship stays yours.
Ask about running costsCustom requirements
A fourth document type, more than 25 fields on one type, a second intake route, or cross-checking extracted values against TMS bookings is outside the Scope Card. Add a note at checkout for a written Change Quote.
Request a custom versionKeep it running
Monthly maintenance covers monitoring, fixes, updates, a health report and change hours each month, enough to handle a new carrier layout, add a field or adjust an exception rule. It starts after the 30 days of support.
$270/mo (5% of the build price a month, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A document capture tool often bills per page or per document | A custom integration is quoted after discovery | Ours is one fixed price, shown on this page before you buy |
| New carrier layouts | Often need a new template each time | Depends on what was built | Ours reads by content, so most new layouts work as they are |
| Exceptions | Results posted whether or not they look right | Depends on the brief | Ours holds unsigned or incomplete paperwork for a person |
| Delivery | Quick to sign up, slow to template | Usually several weeks | Ours has a fixed delivery time shown before you buy, with faster options |
Questions about this product
Which shipping documents can AI Document Extraction for Logistics read?
Up to three document types that you choose, commonly delivery notes, bills of lading and proof-of-delivery scans. Each type can have up to 25 fields. Because extraction reads content rather than fixed positions, the same document type from different carriers usually works without a separate template for each one.
Can it tell when a proof of delivery has no signature?
Yes, if you make signature present one of the fields and set a rule for it. The extraction marks whether a signature appears, and a POD without one is held as an exception for your reviewer rather than written to your TMS as delivered. Rules are agreed with you during intake.
Does the logistics extraction build write into our TMS directly?
Yes, when your TMS or tracking system offers API access and is the destination system. High-confidence fields are written against the right shipment, with a link back to the source document. If your TMS has no usable API, a sheet or Airtable can be the destination instead, with the Google Sheets Sync add-on as one option.
How accurate is it on poor-quality scans?
That is what the 100-document test measures. We run your own samples, including the faded or skewed ones, and the accuracy report shows each field's results. Fields that read poorly get lower confidence scores and go to the review queue, so a bad scan slows one document down instead of corrupting your data.
How long until incoming paperwork is processed automatically?
The delivery time for each speed is in the panel on this page, counted from the day intake is complete and access to your inbox and TMS is verified. Send 20 samples per document type and the field list within 72 hours of ordering, including messy carrier scans. Each day they arrive late moves the go-live date back by 3 working days.
What does logistics document extraction cost per month to run?
Roughly $30 to $200 a month in your own accounts, covering OCR and AI usage plus storage, depending on how many pages pass through. There is no per-document fee from us. Monthly maintenance is optional and covers new carrier layouts and rule changes.
Stop keying shipping paperwork into the TMS by hand.
Order AI Document Extraction for Logistics.
Works well with
Intake & Extraction
AI Document Validation
Checks documents for completeness and consistency against rules.
