A pretrained boarding pass authenticity classifier that sorts an image into one of 2 categories. Use the boarding pass 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 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": "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": "Invalid Boarding Pass",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 2 boarding pass 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.
This function can enhance airport security by instantly verifying the authenticity of boarding passes during check-in and security screenings. This reduces the risk of fraudulent boarding passes being used, thus improving overall passenger safety.
Airlines can integrate this image classification function into their mobile check-in applications to automatically scan and validate the boarding pass images uploaded by passengers. This streamlined process increases user convenience and reduces check-in time.
Travel agencies can utilize this technology to verify the authenticity of boarding passes purchased through their platforms. This ensures that customers are presented with valid tickets, reducing potential loss from fraudulent transactions.
Customer service representatives can use this function to quickly authenticate boarding passes submitted via email or chat for inquiries and support. This expedites resolution times for issues related to ticket validity and enhances overall customer satisfaction.
Airports can implement this classification function at various checkpoints to prevent unauthorized access to restricted areas. Validating boarding passes in real-time can significantly decrease the chances of individuals attempting to bypass security.
Airlines can implement this boarding pass identifier across various platforms, including kiosks, mobile apps, and desktop systems. This ensures consistent service quality and boosts the reliability of boarding pass verification.
Airlines can leverage this function to verify boarding passes for loyalty program benefits, such as upgrades or bonus miles. By ensuring the authenticity of the boarding passes presented, airlines maintain the integrity of their loyalty rewards system.
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 boarding pass 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.