A pretrained country of origin labels classifier that sorts text into one of 10 categories — the country of origin for the given product. Use the country of origin labels 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 44 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": "Argentina",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 country of origin labels 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.
This function can help businesses identify the country of origin for products in their supply chain. By ensuring compliance with regulations and enhancing transparency, companies can bolster consumer trust and make informed sourcing decisions.
E-commerce platforms can use this categorization to automatically tag products with their respective country of origin. This enables consumers to filter products based on origin, allowing for informed purchasing decisions that align with their values, such as supporting local economies or selecting eco-friendly options.
Businesses can analyze trends in consumer preferences concerning products from specific countries. This function aids in identifying shifts in demand for certain regions, informing marketing strategies, and optimizing inventory based on geographic demand.
Companies engaged in international trade can utilize this classification to ensure compliance with customs regulations relating to the country of origin. Accurate classification helps avoid penalties and expedites the import/export processes, facilitating smoother international transactions.
Organizations can leverage the identifier to monitor how products' country of origin impacts brand perception and consumer sentiment. This is important for managing reputation, especially in industries sensitive to sourcing practices, such as food and apparel.
Businesses aiming for sustainability can identify and classify products based on their origin to support sustainable sourcing. This helps companies to align their procurement practices with social responsibility goals and meet consumer demand for ethically sourced products.
Companies can use country of origin labels to tailor marketing strategies based on regional preferences. By understanding consumer attitudes toward products from different regions, businesses can create targeted campaigns that resonate with specific audiences and maximize engagement.
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 country of origin labels 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.