A pretrained tooth types classifier that sorts an image into one of 7 categories — what type of tooth it is. Use the tooth types 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 7 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": "Baby Tooth",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 7 tooth types 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.
Implement a tooth types identifier in dental clinics to assist practitioners in diagnosing oral health issues. By accurately classifying tooth types, the system can suggest potential treatments and highlight leading areas of concern, improving patient outcomes.
Enhance telehealth platforms by utilizing the tooth types identifier to analyze patient-submitted images of their teeth. This capability can provide remote dentists with preliminary insights, allowing them to offer more accurate consultations and treatment recommendations from afar.
Develop an educational application for dental students that employs the tooth types identifier to teach the characteristics and functions of different teeth. Interactive tests using real images can aid learning and retention, fostering better-trained professionals in the industry.
Streamline dental insurance claim processes by integrating the tooth types identifier into claim assessment systems. This can help in automatically verifying the types of treatments performed based on the identified tooth types, reducing fraudulent claims and expediting approvals.
Create a consumer-focused application that analyzes individuals' tooth types to provide customized oral hygiene tips. By targeting specific tooth types, users can receive tailored recommendations for brushing techniques and products suited to their dental needs.
Leverage the tooth types identifier to analyze consumer dental product usage based on tooth types. This data can guide dental product manufacturers in developing targeted marketing strategies and product lines that cater to specific demographics and tooth characteristics.
Assist orthodontic specialists by incorporating the tooth types identifier in treatment planning software. By accurately identifying and categorizing tooth types, orthodontists can create more precise treatment plans and monitor progress more effectively, leading to improved patient satisfaction.
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 tooth types 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.