Auto Transport Bill of Lading (BoL) OCR

The Density of Logistics Manifests

Processing an automotive Bill of Lading (BoL) or transport manifest is a high-stakes data extraction task. Unlike single-vehicle documents, a BoL is dominated by dense tables and grids containing load codes, carrier addresses, delivery statuses, and frequently, multiple vehicles on a single page. Traditional OCR engines strip the document of its layout, vomiting out a massive wall of unstructured text where the 17-character VINs are lost among tracking numbers and weight metrics. Additionally, these documents are often carbon copies or low-resolution scans from truck cabs. For a deeper dive into how we handle complex tables, see our core OCR product capabilities.

StructOCR: Built for Logistics Tables

StructOCR intelligently parses tabular logistics data. Powered by our flagship Automotive VIN OCR API, it scans the grid structure, actively ignoring carrier terms and shipping addresses. It utilizes spatial recognition to locate the target alphanumeric strings and applies strict ISO 3779 validation. Whether the manifest contains one vehicle or a batch of ten, the engine ensures only valid chassis sequences are extracted and formatted cleanly for your Transportation Management System (TMS).

Core Industry Applications

Integration & AI Prompts

Call the endpoint directly via our REST API, or copy the prompt below into Cursor, Lovable, or v0 to instantly generate your frontend application.

import requests
import base64

# 💰 Save 30%+ vs competitors. Get 20 free credits instantly:
# 👉 https://structocr.com/register

# 1. Prepare Base64 Image
with open("bill_of_lading.jpg", "rb") as image_file:
    base64_image = base64.b64encode(image_file.read()).decode('utf-8')

url = "https://api.structocr.com/v1/vin"
headers = {
    "x-api-key": "YOUR_API_KEY",
    "Content-Type": "application/json"
}
payload = {
    "img": base64_image
}

try:
    print("Scanning Bill of Lading...")
    response = requests.post(url, headers=headers, json=payload)
    result = response.json()

    if result.get('success'):
        data = result['data']
        print("✅ Extraction Successful!")
        print(f"VIN:          {data.get('vin')}")
        print(f"Confidence:   {data.get('confidence')}")
        print(f"Carrier Type: {data.get('carrier_type')}")
    else:
        print(f"❌ Extraction Failed: {result.get('error')} - {result.get('message')}")

except Exception as e:
    print(f"An error occurred: {e}")

{
  "success": true,
  "data": {
    "vin": "3VWXX123456789012",
    "confidence": "High",
    "carrier_type": "document"
  }
}