Proof of Delivery OCR API
4.8/5
(30+ reviews)
Proof of delivery OCR API that reads every POD, signed or stamped
Turn signed delivery receipts and carrier PODs, scans or driver photos, into structured JSON. Delivery date, receiver, signature, packages and exceptions, each with a confidence score.
No credit card required
SOC 2 Type II & GDPR

Trusted by finance and product teams at




Why invoices wait on paper PODs
Drivers bring back signed receipts in every format, folded, stamped and annotated. Billing teams scan, read and key each one, then match it to the order before they can invoice.
POD returned
Driver drops signed PODs at the depot.
Batch scanning
Paper sorted and scanned by the batch.
Friction
PODs get lost between truck and office.
Manual keying
Date, receiver and remarks typed in.
Friction
Exceptions stay buried in handwriting.
Order matching
POD matched to the order before billing.
Friction
Invoices wait for missing PODs.
Invoice released
Finally billed, one POD at a time.
Every proof of delivery field you need, as structured JSON
Hover a group to see where it lands in the response. Every value comes back typed, normalised and located on the page, in the schema you defined.
See fields list
Delivery
pod_number, delivery_date, delivery_time
Receiver
receiver_name, signature_present
Delivered to
consignee_name, delivery_address
Shipment
carrier_name, shipper_name, driver_name
References
reference_number
Packages & remarks
package_count, remarks
{
"pod_number": { "value": "RX-88412095" }, "delivery_date": { "value": "2026-10-15" }, "delivery_time": { "value": "14:32" },
"receiver_name": { "value": "M. Torres" }, "signature_present": { "value": true },
"consignee_name": { "value": "Ridgeway Plumbing Supply" }, "delivery_address": { "value": "Dock 4, 900 Industrial Pkwy, Reno, NV" },
"carrier_name": { "value": "Redline Express" }, "shipper_name": { "value": "Atlas Valve Co." }, "driver_name": { "value": "D. Kim" },
"reference_number": { "value": "PO-58213" },
"package_count": { "value": 12 }, "remarks": { "value": "1 carton crushed, contents OK" },
}
Ready to post, not just to read.
Fields come from a data schema you define in minutes. Dates come back in ISO 8601, the signature as true or false, each field with a confidence score.
Built for real PODs, not clean scans
Carbon copies, rubber stamps over the signature, remarks scribbled in the margin, photos taken on a tailgate. The model reads what the receiver wrote and flags what it is unsure of.

Any carrier, any POD format
Signed receipts, carrier PODs and driver-app printouts all look different. They come back in one schema you define, with no template per carrier.

Signatures checked before billing
signature_present comes back true or false with the printed receiver name, so unsigned PODs are caught before you invoice.

Exceptions flagged for claims
Handwritten remarks like "1 carton crushed" come back as text, so damage and shortages reach your claims team the same day.

Driver photos cropped and read
Drivers photograph PODs on a tailgate. Mindee detects the page in the photo, crops it and extracts it like a clean scan.
PDF / JPEG / PNG / WEBP / TIFF / HEIC, Signed receipts & carrier PODs, Stamps & signatures, Handwritten remarks, Driver phone photos
POD OCR accuracy you can measure, field by field
Every field comes with a confidence score, so clean PODs release invoices automatically and unclear handwriting goes to a reviewer. Test it on your own PODs in the free trial.
96.4%
Field-level accuracy on printed fields
POD number, date, consignee
92.1
Accuracy on signature detection
Signed, stamped, missing
0.9s
Median time per POD
Single page, synchronous call
A confidence score on every field
Send only real exceptions to a human

Document AI features, better than OCR
Prepare, classify and extract. Mindee delivers high-accuracy extraction for every document format, so you can automate workflows with speed and high reliability.
Data extractor
Classifier
Splitter
Edge detector
Pull the exact fields you need from any document
Pick a ready-made model or describe your own data schema. Every value comes back typed, normalised, located on the page and scored.
- Prebuilt models or your own custom schema
- Tables and line items, across pages
Know what each document is before you read it
The classifier labels every upload with your own classes, so an ID card goes to onboarding and an invoice goes to accounts payable.
- Your own document classes
- Route each type to the right model
One scanned batch in, separate documents out
Send a long PDF from the office scanner. Mindee finds where each document starts and ends, and returns them one by one.
- Page ranges for every detected document
- Up to 200 pages and 100 MB per file
Several documents on one photo? Each gets its own crop
Users photograph three receipts on a desk, or both sides of an ID. Mindee detects each border, returns its coordinates and reads them separately.
- Coordinates for every detected document
- Built for mobile capture flows
Prototype in minutes, go live with the API
Step 1 : Prototype
Run a proof of concept in Make, Zapier or n8n
No code, no IT ticket. Point a mailbox at Mindee and watch the data arrive in a spreadsheet.
POD captured
Driver photo, scan or email
Mindee reads the POD
Receiver, signature, remarks
Invoice released
Your TMS, ERP or Sheets
Low-confidence fields sent for review
Slack or email alert to your team
Step 2 : Production
Integrate the API into your platform
Official SDKs, typed responses and webhooks for async processing. Most teams ship the integration in a day.
mindee docs
$ pip install mindee
Your app
Mindee API
Your ERP/CRM
.webp)
Integrate Mindee into your workflow in minutes with SDKs & no-code tools
Go live in minutes using our verified Zapier & Make.com app with zero coding, or integrate seamlessly via our well-documented REST API built for developers. SDKs available for Python, .NET, Node.JS, Java, Ruby, PHP.
Integrations

Enterprise-grade security
Our API has a SOC 2 Type II certified infrastructure and is GDPR Compliant to ensure your file information remains protected at all times.
EU or US hosting available
GDPR, CCPA Compliant
Learn more
What teams build with proof of delivery OCR
The same API powers very different products. Here is where it usually starts.

Finance & Accounting
Accounts payable
Extract, match and post supplier invoices without manual data entry.

Logistics
Customs clearance
Capture shipping and customs data across every document of a shipment.

Insurance
Claim management
Read the documents attached to each claim and route the file to the right handler.
Rated 4.8/5 by developers and operations teams
4.8
4.9
Mindee is a web based tool that help us in scanning and reading different type of documents like identity cards, invoices, proposal plans etc and extract all the information with its AI and then it provides all the information and data associated with these documents a structured way.
Mindee is a web based tool that help us in scanning and reading different type of documents like identity cards, invoices, proposal plans etc and extract all the information with its AI and then it provides all the information and data associated with these documents a structured way.
Mindee is a software that helps us to convert all of our physical business data like bills, invoices, warranty cards, calendar, recipts received to us into a digital documents that can be stored in our drive and can be uploaded in different type of Excel sheets so that all the updates can be maintained and a proper analytics of transactions can be kept by the financial team
I like the easiness and how to use it. Also the price model is very fair. Good with space for improvement
Documents related that Mindee reads
FAQ about Mindee's Proof of Delivery OCR API
Can't find what you're looking for? Our team answers within one business day.
What is a proof of delivery?
A proof of delivery (POD) is the document that confirms a shipment reached its destination. It is usually signed by the person who received the goods and records the delivery date and time, the receiver’s name, the delivery address, the number of packages and any remarks about damage or shortages. Carriers and shippers use it to close the shipment, send the invoice and support claims or disputes. PODs can be paper receipts signed on the spot or electronic records captured in a driver app. With Mindee, you define the POD fields you need in a data schema, and each delivery receipt, scan or driver photo comes back as structured JSON with a confidence score for every field.
What’s the difference between a delivery note, a proof of delivery and a bill of lading?
A delivery note travels with the goods and lists what is being delivered. It is issued by the seller or the shipper. Once the recipient signs it to confirm receipt, often adding remarks, it becomes a proof of delivery. A bill of lading is different: it confirms that the carrier received the goods at loading, but not that they reached the recipient. Mindee recognizes each of these documents, even when they arrive together, so each one goes to the right step of your process.
Can Mindee read handwritten remarks, signatures and stamps on PODs?
Yes. PODs are often signed on the spot, stamped, annotated by hand and photographed by drivers in poor conditions. Mindee reads both printed and handwritten content, detects whether the document is signed or stamped, and extracts handwritten remarks such as “2 cartons damaged” or corrected quantities. These remarks are the key information in a delivery dispute. PODs with reservations or unclear fields can be flagged automatically and sent to your team, while clean deliveries are processed straight away.
How does POD automation speed up invoicing and payments?
Carriers and logistics providers often can’t invoice a delivery until they have received and checked the signed POD. When thousands of PODs arrive as paper or photos, this can delay invoicing by days or weeks. With Mindee, each POD is processed as soon as it is uploaded: the shipment reference, delivery date and signature are checked automatically, and the invoice can be issued right away. On the shipper side, the POD serves as the goods receipt in three-way matching, alongside the purchase order and the invoice, so payment can be approved without manual checks.
About Mindee
Is my data secured and protected during the conversion process?
Yes, your data is highly secured and protected during the entire conversion process. As an enterprise-grade OCR solution, Mindee takes data privacy very seriously. Here are the key security measures in place:
- Certified compliance: Mindee's infrastructure is SOC 2 Type II certified and fully GDPR compliant, ensuring strict industry standards for data protection.
- Encryption: All documents and extracted data are fully encrypted both in transit (during the API call) and at rest.
- Data localization: You have control over where your data is processed, with the option to host and process your data on either EU or US servers.
- Strict privacy: Mindee respects data confidentiality. Your processed documents are not shared with third parties, and your private data is not used to train global AI models.
In short, your sensitive documents are processed in a secure, isolated environment and remain completely under your control.
Is Mindee's OCR API free to use?
We provide a 14 days free trial so you can fully test any of our OCR models — no credit card required. After this, we offer different pricing tiers depending of the volume of pages processed and the features you might need. See the pricing page for more information.
What file formats are supported for JSON conversion?
The supported document formats are:
- PDF (
application/pdf) – While technically a document format rather than an image, it is natively supported for all extraction models. - JPEG / JPG (
image/jpeg) - PNG (
image/png) – Must be non-animated. - WebP (
image/webp) - TIFF / TIF (
image/tiff) – Both single-page and multi-page TIFFs are supported and processed similarly to PDFs. - HEIC (
image/heic) – Apple's High-Efficiency Image Container format.
📌 Important technical limitations to keep in mind:
To ensure the OCR pipeline runs smoothly and successfully returns your JSON, make sure your files adhere to the following constraints:
- Maximum file size: 100 MB per file.
- Maximum page count: Up to 200 pages per document.
- File state: The files cannot be encrypted, and PDFs must not be password-protected.
Ready to stop keying PODs?
Build your POD model from a sample in minutes and send your first delivery receipt to the API, with a team of document processing engineers behind it.
14-day free trial
No credit card required