A pretrained bat species classifier that sorts an image into one of 2 categories — which species of bat it is. Use the bat species 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 40 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.
Get your own copy of this classifier behind your own endpoint — callable from any HTTP client:
curl -X POST "https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{"data": "https://example.com/photo.jpg"}'import requests
response = requests.post(
"https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke",
headers={"Authorization": "Bearer YOUR_ACCESS_TOKEN"},
json={"data": "https://example.com/photo.jpg"},
)
print(response.json())const response = await fetch("https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_ACCESS_TOKEN",
"Content-Type": "application/json",
},
body: JSON.stringify({ data: "https://example.com/photo.jpg" }),
});
console.log(await response.json());$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://www.nyckel.com/v1/functions/YOUR_FUNCTION_ID/invoke');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
curl_setopt($ch, CURLOPT_POST, 1);
curl_setopt($ch, CURLOPT_POSTFIELDS, '{"data": "https://example.com/photo.jpg"}');
$headers = array();
$headers[] = 'Authorization: Bearer YOUR_ACCESS_TOKEN';
$headers[] = 'Content-Type: application/json';
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
$result = curl_exec($ch);
curl_close($ch);
echo $result;Example response
{
"labelName": "Little Brown Bat",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 2 bat species 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.
For businesses in the ecotourism sector, a 'bat species' identifier tool can be used to differentiate and provide accurate information about the various bat species encountered during tours. This will enhance the clients' experience by enriching their knowledge of the ecosystem.
Pest control companies could use the function to accurately identify bat species that may be seen as pests in certain locations. With accurate classification, appropriate and species-specific management plans can be determined.
Agencies focused on wildlife conservation can use the bat species identifier to monitor the population levels of different bat species. By identifying the species, they can track migratory patterns, reproduction rates, and potential threats to different bat populations.
Veterinary clinics specializing in wildlife can utilize the bat species identifier to diagnose and treat diseases more effectively. By knowing precisely what bat species they are dealing with, vets can tailor treatments and care plans to the specific needs of the species.
Research institutions studying bats can use the function to simplify and increase the accuracy of their fieldwork. Automatic identification of vast numbers of bats on images can help researchers to save precious time and focus on interpreting the collected data.
Zoos can use the bat species identifier to provide educational information to visitors about the various types of bats. This function may also assist in the identification and tracking of specific bats within a zoo's collection, improving their management and care.
Companies working with bioacoustics can use the tool to enhance their software capabilities, offering more comprehensive analyses. By differentiating bat species visually, it can complement and cross-verify their acoustic analysis.
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 bat species 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.