Give freight audit analysts charge rows they can actually compare
For Freight audit analysts and transportation finance teams
Prepare a carrier invoice for your audit process by extracting its shipment references and individually labeled charge rows. Preserve the printed amounts and currency so your analysts can compare them with agreements and operational records in their own systems.
25 free credits/month · No card needed
See the workflow and review checks{
"carrier_name": "Example Freight Lines",
"invoice_number": "DEMO-FI-482",
"invoice_date": "2026-08-20",
"shipment_references": [
{
"label": "BOL",
"value": "DEMO-BOL-1048"
}
],
"currency": "USD",
"charge_rows": [
{
"description": "Linehaul",
"amount": 850
},
{
"description": "Fuel surcharge",
"amount": 136
},
{
"description": "Liftgate delivery",
"amount": 65
}
],
"invoice_total": 1051
}Synthetic data, not a live extraction. Real responses also include confidence, validation, and result status.
When this work lands on your desk
A carrier invoice enters the audit queue and an analyst needs its charge details before checking the applicable rate and shipment record.
A total alone cannot explain an invoice. Linehaul, fuel, and accessorial charges may appear in a compact table with credits or adjustments elsewhere on the page. Carrier-specific reference labels make it easy to copy an invoice number into a shipment field or combine unrelated charge rows.
Start with the documents you already collect
- Carrier freight invoice PDFs
- Scanned transportation invoices
- Carrier credit and adjustment documents
PDF, JPEG, PNG, TIFF, or WEBP. Send one file per extraction call; create separate schemas when the document types need different fields.
Define the fields
Open the starter schema. Edit field descriptions, mark the values your process requires, and save it in your account.
Extract at intake
Send the document and saved schema slug to
POST /api/v1/extract, or collect the file through a branded upload site.Hand off reviewed data
Your audit application matches reviewed references, applies contractual rates, checks duplicates, and routes disputed charges. Dokyumi supplies the document fields; it does not rate shipments or decide which charges should be paid.
A schema shaped around the next step.
Start with these fields, then adjust them to match your documents and destination system. The example above shows the data object you are asking Dokyumi to extract.
Download editable starter schemaStarter fields are optional until you choose which are required. Nested line items need a defined structure if you want validation of their individual values.
| Field | Type | What to capture |
|---|---|---|
carrier_name | string | Invoice issuer as printed. |
invoice_number | string | Preserve prefixes and leading zeros. |
invoice_date | date | Issue date rather than shipment date. |
shipment_references | array | Reference label and value pairs for downstream matching. |
currency | string | Printed currency; ambiguous symbols need review. |
charge_rows | array | Printed description, amount, and any supplied quantity or rate. |
invoice_total | currency | Total as shown, preserving a credit or negative sign. |
Give exceptions a clear path to review.
Dokyumi returns a model-reported confidence map, validation details, and a completed or review status for produced results. Check required fields and your business rules before passing data onward.
A completed extraction describes the extraction result. Your application and reviewers own matching, approvals, routing, and updates to other systems.
Read the response contractChecks for this process
- Inspect credits, revised invoices, and negative line items before calculating downstream totals.
- Keep the carrier’s accessorial wording available when mapping internal charge codes.
- Use your own arithmetic checks to compare extracted rows with the printed total and investigate differences.
Prove the fit on a representative batch.
Evaluate invoices from a small carrier set with fuel, at least one accessorial, and an adjustment example. Track line-item corrections and how much analyst preparation remains before your existing audit rules can run.
Compare extracted values with a reviewer’s reference set. Record corrections, unresolved fields, review time, and credits used before connecting downstream actions.
The free plan’s credit limits apply. Assisted pilots are scoped with Dokyumi before work begins.
Expand when the next process is ready
Upgrade as invoice volume grows, then add schemas for carrier-specific details and supporting BOL or delivery records. More upload sites can separate submission channels for customer accounts or operating units.
For a tailored implementation
Discuss custom volume or a wider schema rollout when transportation audit becomes a shared service across many business units.
Talk through document mix and volumeStart small. Add capacity as intake grows.
All self-service plans include the REST API, upload-site webhooks, custom confidence thresholds, and schema inference. Choose by volume, schema count, and upload sites.
Each document uses one credit per 5 pages, rounded up. An 8-page file uses 2 credits. Self-service files can be up to 50 pages; larger files, custom-built schemas, and additional volume are quoted through Enterprise. Full pricing details
Questions about freight invoice audit preparation
Does Dokyumi perform a freight audit?
It prepares structured invoice data. Rate agreements, shipment matching, duplicate checks, tolerance rules, and payment decisions stay in your audit process.
Can it extract fuel and accessorial charges separately?
Request an array of charge rows that retains each printed description and amount. Test invoices where charges wrap across lines or appear in separate sections.
How should consolidated invoices be handled?
Design a schema with shipment sections and nested charge details when needed. Evaluate a representative file within supported limits before processing consolidated statements at scale.
How do I test this workflow on my own documents?
Start free with 25 credits per month, 2 schemas, and 1 branded upload site. The starter schema opens in the schema builder after sign-up. Edit the fields, save it, and upload a representative file through your account or the extraction API. Account documents are stored according to Dokyumi’s privacy policy; contact hello@dokyumi.com for deletion requests and retention requirements.