A pretrained mrz validity classifier that sorts text into one of 2 categories. Use the mrz validity API immediately, no training required, then adapt it to your own data when you need more.
Drop in some text and get the prediction back. No signup, no setup.
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.
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": "The text you want to classify"}'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": "The text you want to classify"},
)
print(response.json())Example response
{
"labelName": "Invalid Mrz",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 2 mrz validity categories, served on Nyckel's own infrastructure — your text snippet stays on Nyckel.
Send raw text 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.
The 'mrz validity' identifier can be utilized at border control checkpoints to automate the verification of travel document authenticity. By quickly classifying the validity of Machine Readable Zones (MRZ), border authorities can streamline the process of passenger verification and reduce wait times.
Financial institutions can use the 'mrz validity' function to validate identity documents submitted by customers during onboarding processes. This reduces the risk of identity fraud by ensuring that documents are legitimate and have not been tampered with.
Organizations that require secure access can implement the 'mrz validity' identifier to verify employee identification badges quickly. This ensures that only authorized personnel enter sensitive areas, enhancing overall security protocols.
Online travel agencies can integrate the 'mrz validity' feature to validate customer travel documents during booking processes. By ensuring the correctness of MRZ data upfront, companies can reduce errors leading to complications during travel.
Software applications that require document uploads, such as government portals or e-commerce sites, can implement this function to check the validity of IDs or passports during user verification. This simplifies the document validation process and increases operational efficiency.
Mobile applications specializing in identity verification can leverage the 'mrz validity' identifier to enhance user trust and security. Users can quickly verify the legitimacy of their ID or passport when accessing services or features, improving the app's reliability.
Event organizers can use the 'mrz validity' functionality at conferences or large gatherings to authenticate attendees' identification documents at registration points. This helps manage attendee access smoothly and curbs unauthorized entry effectively.
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 text samples 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 mrz validity 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.