A pretrained diploma authenticity classifier that sorts an image into one of 10 categories — the authenticity status of a diploma. Use the diploma authenticity API immediately, no training required, then adapt it to your own data when you need more.
Drop in a photo and get the prediction back. No signup, no setup.
A sample of the 24 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.
Once you've added this classifier to your console, you get your own copy of it behind your own endpoint. Invoke it with any HTTP client:
curl
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer $NYCKEL_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "https://example.com/photo.jpg"}'Python
import requests
# Get an access token: https://www.nyckel.com/docs/api/overview/authentication/
token = "YOUR_ACCESS_TOKEN"
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer " + token},
json={"data": "https://example.com/photo.jpg"},
)
print(response.json())Example response
{
"labelName": "Authentic",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 diploma authenticity 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.
Educational institutions can utilize the diploma authenticity identifier to verify the legitimacy of diplomas submitted by prospective students. This ensures that only qualified individuals are admitted into programs, reducing the risk of enrolling unqualified candidates.
Employers can implement the diploma authenticity function during the hiring process to authenticate candidates' claimed educational qualifications. This helps to mitigate the risk of hiring individuals with falsified diplomas, thus maintaining workforce integrity.
Accreditation agencies can use the diploma verification function to cross-check institutions' issued diplomas against national databases. This ensures that accredited institutions are genuinely producing graduates, maintaining oversight and quality assurance in the education sector.
Licensing boards can apply the diploma authenticity identifier to verify educational credentials required for licensing professionals. This helps to prevent fraud in fields where specific educational backgrounds are mandatory, such as law, medicine, and engineering.
Alumni associations can leverage the diploma verification function to ensure that only legitimate graduates are admitted into their networks. This maintains the credibility of the alumni community and enhances networking opportunities among verified graduates.
Online educational platforms can use this verification function to authenticate diplomas issued in their programs before students can claim or publish their qualifications. This fosters trust in the platform and enhances the value of the credentials offered.
Government agencies can incorporate diploma authenticity checks when hiring for public sector roles. This ensures compliance with educational requirements, enhances the credibility of government staff, and promotes transparency in the hiring process.
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.
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.
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.
No. This diploma authenticity 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.
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.
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.