Identify if drivers license number is in a scan using AI

Below is a free classifier to identify if drivers license number is in a scan. Just input your text, and our AI will predict if the driver's license number is valid - in just seconds.

if drivers license number is in a scan identifier

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    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("if-drivers-license-number-is-in-a-scan", "your_text_here", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/if-drivers-license-number-is-in-a-scan/invoke', {
        method: 'POST',
        headers: {
            'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
            'Content-Type': 'application/json',
        },
        body: JSON.stringify(
            {"data": "your_text_here"}
        )
    })
    .then(response => response.json())
    .then(data => console.log(data));
                

    curl -X POST \
        -H "Content-Type: application/json" \
        -H "Authorization: Bearer YOUR_BEARER_TOKEN" \
        -d '{"data": "your_text_here"}' \
        https://www.nyckel.com/v1/functions/if-drivers-license-number-is-in-a-scan/invoke
                

How this classifier works

To start, input the text that you'd like analyzed. Our AI tool will then predict if the driver's license number is valid.

This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Contains Drivers License Number and Does Not Contain Drivers License Number.

We'll also show a confidence score (the higher the number, the more confident the AI model is around if the driver's license number is valid).

Whether you're just curious or building if drivers license number is in a scan detection into your application, we hope our classifier proves helpful.

Recommended Classifiers

Need to identify if drivers license number is in a scan at scale?

Get API or Zapier access to this classifier for free. It's perfect for:



  • Fraud Detection in Document Processing: This use case involves scanning documents for driver’s license numbers to identify potential fraudulent activities. By flagging documents that contain such information without proper justification, organizations can mitigate risks associated with identity theft and unauthorized access.

  • Automated Compliance Checks: Companies in regulated industries can utilize this classification function to ensure that driver’s license numbers are only present in authorized documents. This automated scanning process can streamline compliance audits and reduce the likelihood of human error in document review.

  • Customer Verification in Financial Services: Financial institutions can implement this functionality to quickly verify customer identities during account opening. By ensuring that a legitimate driver's license number is scanned, they can enhance security measures and accelerate customer onboarding processes.

  • Insurance Claim Processing: In insurance companies, this function can be used to identify driver’s license numbers in claims documents. It helps ensure that claims are processed for valid policyholders, reducing the chances of fraudulent claims and assisting in risk assessment.

  • Law Enforcement Record Management: Law enforcement agencies can employ this text classification in managing various records and reports. By automatically identifying driver’s license numbers in investigations, agencies can enhance their data management efforts and improve case tracking capabilities.

  • Ride-Sharing Driver Verification: Ride-sharing platforms can use this technology to scan drivers’ submitted documentation to confirm that they hold valid licenses. This function helps maintain safety standards and regulatory compliance for drivers operating within the platform.

  • Public Safety Monitoring: City or state safety departments can use this classification tool to analyze scanned documents for driver’s license numbers during traffic stops or inspections. This helps to ensure that drivers on the road are licensed, thereby promoting public safety and reducing illegal driving incidents.

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