Help carrier billing teams review the delivery receipt before invoicing
For Carrier billing desks and freight accounts receivable teams
Extract the delivery references and receiving details that a billing reviewer needs from a POD image or PDF. Build a structured record alongside the original receipt, then let your existing process determine whether the billing package is ready.
25 free credits/month · No card needed
See the workflow and review checks{
"shipment_reference": "DEMO-BOL-1048",
"delivery_date": "2026-08-18",
"delivery_time_text": "09:35",
"consignee": "Example Destination Warehouse",
"received_quantity": 80,
"quantity_unit": "cartons",
"exception_notes": "Receiver note: two outer cartons dented."
}Synthetic data, not a live extraction. Real responses also include confidence, validation, and result status.
When this work lands on your desk
A driver or customer submits a delivery receipt, and the billing desk needs to connect it to the load awaiting an invoice.
Receipts arrive as rotated photos, scanned copies, and annotated bills of lading. A receiving date may sit beside a shipping date, and shortage notes may appear below the main table. Searching each file for a load reference and legible receiving information slows the billing queue.
Start with the documents you already collect
- Proof of delivery PDFs
- Scanned delivery receipts
- Images of annotated delivery paperwork
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
The billing reviewer checks the receipt and associates it with the shipment in the customer’s system. Customer-owned rules decide document completeness, exception follow-up, and invoice release; extraction does not perform these checks.
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 |
|---|---|---|
shipment_reference | string | Visible load, BOL, or delivery reference specified by your schema. |
delivery_date | date | Recorded delivery date, when legible. |
delivery_time_text | string | Preserve the printed time and any stated time zone. |
consignee | string | Receiving business or location shown on the receipt. |
received_quantity | number | Explicit received quantity; do not substitute shipped quantity. |
quantity_unit | string | Pallets, cartons, or another unit as written. |
exception_notes | string | Visible shortage or damage notes without interpreting liability. |
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
- Compare delivery and shipment dates where both appear on the page.
- Check handwritten quantities and exception notes against the image.
- Resolve references in your shipment system rather than assuming that similar identifiers belong to the same load.
Prove the fit on a representative batch.
Sample the receipt formats that actually delay your billing desk. Include a clean POD, a phone photo, and one with a visible exception note; measure how often the reviewer must reopen the source to correct the extracted fields.
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
Recurring delivery volume creates a reason for more credits. Expand into BOL and invoice schemas to prepare additional billing-package data, and use branded upload sites when multiple fleets or customer groups submit receipts.
For a tailored implementation
Consider a custom plan for high-volume receipt processing or a broad customer-portal rollout after validating the review process.
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 proof of delivery billing preparation
Does it authenticate a delivery signature?
No. Extraction does not authenticate signatures, identities, or delivery. A reviewer must decide whether the submitted record meets the customer’s billing requirements.
Can I use a photo taken by a driver?
Supported image formats can be submitted to the extraction endpoint. Evaluate lighting, cropping, handwriting, and blur on representative driver photos before relying on the fields.
Will it release invoices automatically?
Dokyumi returns JSON. Any association with a shipment and any invoice-release logic must be implemented and controlled in your billing workflow.
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.