Identify if number is in an email using AI

Below is a free classifier to identify if number is in an email. Just input your text, and our AI will predict if a number is present in the email - in just seconds.

if number is in an email identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("if-number-is-in-an-email", "your_text_here", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/if-number-is-in-an-email/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-number-is-in-an-email/invoke
                

How this classifier works

To start, input the text that you'd like analyzed. Our AI tool will then predict if a number is present in the email.

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

We'll also show a confidence score (the higher the number, the more confident the AI model is around if a number is present in the email).

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

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Need to identify if number is in an email at scale?

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



  • Spam Detection: This function can be employed in email filtering systems to identify and classify spam emails, particularly those that contain misleading numbers or financial details. By flagging such emails, businesses can enhance their email security and reduce the risk of phishing attacks.

  • Order Confirmation Monitoring: E-commerce platforms can use this text classification function to automatically identify and extract order confirmation emails, particularly those with associated order numbers. This ensures timely processing and fulfillment of customer orders, improving overall customer satisfaction.

  • Customer Support Automation: Customer support systems can utilize this function to quickly detect emails containing ticket numbers or case identifiers. This allows for automated routing and prioritization of support requests, leading to more efficient response times and service quality.

  • Invoice Processing: In accounting or finance departments, this function can help identify emails containing invoice numbers. By automating the extraction of these numbers, businesses can streamline their accounts payable processes and improve payment tracking.

  • Lead Generation Tracking: Marketing teams can leverage this function to classify emails that contain unique lead identifiers or promotional codes. This can help in tracking the effectiveness of marketing campaigns and optimizing future outreach strategies.

  • Fraud Detection: Financial institutions can deploy this function to flag emails that contain suspicious transaction or account numbers. By monitoring these elements, banks can enhance their fraud detection capabilities and take proactive measures to protect customers.

  • Telecom Query Resolution: Telecom companies can use this function in customer service workflows to identify emails related to customer accounts or service requests that include service numbers. This helps in efficiently matching customer inquiries to the right service records, improving resolution times.

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