Fleet Driver Onboarding with PDF417 and AAMVA Data

The Data-Entry Problem in fleet administration

Fleet teams receive licenses from many locations and then normalize dates, classes, restrictions, and endorsements by hand. Teams also need to distinguish a readable barcode from a verified person or authentic credential; combining those concepts creates compliance and product risk.

Deterministic Barcode Parsing with Human Confirmation

Send the license-back image through a server-side onboarding service, store normalized fields in the candidate record, and retain a separate approval decision. StructOCR's driver license PDF417 API decodes the barcode and parses the AAMVA record without asking a generative model to reconstruct unreadable values. Use authoritative motor-vehicle records and your compliance process for eligibility decisions; PDF417 parsing is a data-capture step.

Workflow Applications

Server-Side PDF417 Integration

Send the complete license-back image from a protected backend. This example selects fields relevant to fleet administration and handles HTTP 422 as a retake or review state.

import base64
import os
import requests

with open("license-back.jpg", "rb") as image_file:
    image = base64.b64encode(image_file.read()).decode("ascii")

response = requests.post(
    "https://api.structocr.com/v1/driver-license-pdf417",
    headers={"x-api-key": os.environ["STRUCTOCR_API_KEY"]},
    json={"img": image},
    timeout=30,
)

if response.status_code == 422:
    print("Retake or review:", response.json().get("error"))
else:
    response.raise_for_status()
    data = response.json()["data"]
    print("vehicle_class:", data.get("vehicle_class"))
    print("restrictions:", data.get("restrictions"))
    print("endorsements:", data.get("endorsements"))

{
  "success": true,
  "data": {
    "type": "drivers_license",
    "source": "pdf417",
    "country_code": "USA",
    "region": "CA",
    "document_number": "SAMPLE1234",
    "surname": "SAMPLE",
    "given_names": "ALEX MORGAN",
    "first_name": "ALEX",
    "middle_name": "MORGAN",
    "sex": "X",
    "date_of_birth": "1990-01-15",
    "date_of_issue": "2025-01-15",
    "date_of_expiry": "2030-01-15",
    "address": "100 EXAMPLE AVE",
    "city": "SAMPLE CITY",
    "postal_code": "00000",
    "vehicle_class": "C",
    "restrictions": null,
    "endorsements": null,
    "document_discriminator": "SAMPLE-DISCRIMINATOR",
    "issuer_identification_number": null,
    "aamva_version": 10,
    "jurisdiction_version": 0
  }
}