Pretrained computer vision classifier
Identify if the letterhead is real with one API call.
A pretrained if the letterhead is real classifier that sorts an image into one of 2 categories. Use the if the letterhead is real API immediately, no training required, then adapt it to your own data when you need more.
Try the if the letterhead is real classifier
Drop in a photo and get the prediction back. No signup, no setup.
What this if the letterhead is real classifier recognizes
A sample of the 2 labels this pretrained classifier chooses between.
Need a label that isn't here? Clone the classifier into your Nyckel console and edit the label set to fit your data.
Call the if the letterhead is real API
Get your own copy of this classifier behind your own endpoint — callable from any HTTP client:
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "https://example.com/photo.jpg"}'import requests
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer YOUR_ACCESS_TOKEN"},
json={"data": "https://example.com/photo.jpg"},
)
print(response.json())const response = await fetch("https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_ACCESS_TOKEN",
"Content-Type": "application/json",
},
body: JSON.stringify({ data: "https://example.com/photo.jpg" }),
});
console.log(await response.json());$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
curl_setopt($ch, CURLOPT_POST, 1);
curl_setopt($ch, CURLOPT_POSTFIELDS, '{"data": "https://example.com/photo.jpg"}');
$headers = array();
$headers[] = 'Authorization: Bearer YOUR_ACCESS_TOKEN';
$headers[] = 'Content-Type: application/json';
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
$result = curl_exec($ch);
curl_close($ch);
echo $result;Example response
{
"labelName": "Fake Letterhead",
"labelId": "label_...",
"confidence": 0.92
}Under the hood
Trained on a Nyckel-curated dataset covering 2 if the letterhead is real categories, served on Nyckel's own infrastructure — your image stays on Nyckel.
Send an image URL or file to the invoke endpoint; the response is a label with a confidence score.
Clone it, then correct predictions and add your own samples in the console — Nyckel retrains automatically, turning this into a custom model tuned to your data.
Where teams use if the letterhead is real classification
Fraud Detection in Corporate Communication
This function can be employed by businesses to automatically verify the authenticity of letterheads in correspondence. This can help in identifying fraudulent emails or documents, thus protecting the company from scams.
Legal Document Verification
Law firms can utilize this identifier to confirm the legitimacy of documents sent by clients or opposing parties. By validating the letterhead, they can ensure that the communication is genuine, preventing potential legal disputes arising from false documents.
Procurement Process Validation
In procurement, companies can use this function to verify letters from suppliers or vendors. Ensuring that letterheads are genuine helps in maintaining trust in supplier relationships and reducing the risk of contracts based on fraudulent representations.
Compliance and Regulatory Audits
Organizations in regulated industries can leverage this identifier during compliance checks to ensure that all official communications adhere to required standards. It helps in maintaining a clear and auditable trail of communications with authentic validations.
Customer Support Verification
Customer support teams can use this function to verify customer communications that come in the form of official letters or claims. By confirming the authenticity of letterheads, they can avoid processing fraudulent claims and maintain the integrity of their support services.
Academic Credential Verification
Educational institutions can implement this identifier to validate the authenticity of letters or documents received from applicants or alumni. This helps in preventing fraud related to academic credentials and ensures that the institution maintains its standards.
Event Registration and Invitation Validation
Organizations hosting events can use this function to verify the legitimacy of letters or invitations sent for attendance or participation. This ensures that responses to invitations are from genuine sources, thereby enhancing the security and exclusivity of the event.
Common questions
What's the difference between a zero-shot and a Nyckel-trained classifier?
A zero-shot classifier uses a large foundation model's general knowledge to pick between your labels — no task-specific training, so new or edited labels work immediately. A Nyckel-trained classifier has been trained on labeled examples and runs on Nyckel's own infrastructure, which typically makes it faster, cheaper per call, and more accurate on data that resembles its training set. The "Under the hood" section on this page shows which kind this classifier is, and any classifier can be adapted into a trained one by adding your own examples.
How do I know whether this will work for my application?
Honestly: we can't know in advance — it depends on your data stream and how closely it resembles what this classifier has seen. The reliable way to find out is to measure it on your own data: start invoking the classifier with real traffic, or upload and annotate a set of images in the console — make sure they look like your production data, not idealized examples. Nyckel's evaluation metrics then show you exactly how it performs on that data before you rely on it.
What happens when it makes a mistake?
No classifier is perfect, so Nyckel is built around the correction loop: invokes can be captured for review, you confirm or correct predictions in the console, and corrections become training data. Over time the model adapts to your data distribution — accuracy on your traffic improves with use rather than staying fixed.
Do I need training data to get started?
No. This if the letterhead is real classifier works out of the box — clone it into your console and you'll have your own API endpoint in under a minute. Training data only enters the picture when you want to adapt it: your corrected predictions and uploaded samples improve the model, and you can also edit the label set to match your needs.
What does it cost to try?
Trying the classifier on this page is free with no signup. Cloning it requires a free account, and the free tier covers your first API calls each month — see nyckel.com/pricing for current limits and paid tiers.
Related classifiers
Ready to classify if the letterhead is real at scale?
Add this pretrained classifier to your Nyckel console — you'll get a live API endpoint in under a minute, and a path to a custom model when you need one.