Auto Repair Invoice (RO) VIN Extraction

The Reality of Body Shop Paperwork

Extracting vehicle data from the automotive aftermarket is incredibly messy. Independent mechanic shops and collision centers generate Repair Orders (ROs) and invoices using thousands of different software systems, meaning there is zero layout standardization. Physically, these documents endure harsh environments: they are printed on fading thermal paper, get crumpled in technician clipboards, and are frequently covered in oil or grease stains. Standard template-based OCR completely collapses when faced with a greasy, crumpled invoice that lacks a predictable structure. For a deeper dive into how we handle physical document degradation, see our core OCR product capabilities.

StructOCR: Built for the Shop Floor

StructOCR brings enterprise-grade extraction to the messy shop floor. Powered by our flagship Automotive VIN OCR API, it abandons rigid templates entirely. The engine scans the disorganized invoice, ignoring parts lists, labor hours, and customer details. It utilizes advanced contrast normalization to read through grease stains and faded thermal ink. By applying strict ISO 3779 validation, it anchors directly to the 17-character vehicle identifier, digitizing the core asset instantly.

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("repair_invoice.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 Auto Repair Invoice...")
    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": "JTNBX32R1A1234567",
    "confidence": "High",
    "carrier_type": "document"
  }
}