A pretrained plumbing type classifier that sorts an image into one of 10 categories — the type of plumbing system in the image. Use the plumbing type 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 24 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": "Acrylic",
"labelId": "label_...",
"confidence": 0.92
}Trained on a Nyckel-curated dataset covering 10 plumbing type 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.
Utilize the plumbing type identifier to categorize service calls based on the type of plumbing issue reported. By identifying whether the issue pertains to residential, commercial, or industrial plumbing, companies can allocate resources more efficiently and ensure that skilled technicians are dispatched for specific tasks.
Implement plumbing type identification to optimize inventory levels based on the type of plumbing projects underway. By predicting demand for different plumbing supplies according to service types, businesses can reduce excess inventory costs and improve supply chain efficiency.
Leverage plumbing type classification to develop marketing campaigns tailored to specific customer segments. By understanding which types of plumbing services are most frequently requested, companies can create targeted advertisements and promotions that resonate with different demographics, increasing engagement and conversion rates.
Use the plumbing type identifier to assess technician performance and identify training needs. By analyzing common service requests and errors per plumbing type, companies can create customized training programs that enhance technician skills in specific areas, improving service quality and customer satisfaction.
Implement the plumbing type classifier in quality assurance processes to monitor repairs and installations. By categorizing completed jobs by plumbing type, companies can assess if service standards are being met consistently, ensuring adherence to regulatory compliance and reducing liability risks.
Integrate plumbing type identification into CRM systems to enhance customer interactions. By understanding customers' previous service types, companies can personalize follow-ups, maintenance reminders, and upsell opportunities, fostering long-term relationships and loyalty.
Utilize the plumbing type identifier to analyze historical data for predictive maintenance scheduling. By identifying trends and common issues associated with different plumbing types, businesses can proactively address potential failures, minimizing downtime and extending the lifespan of plumbing systems.
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 plumbing type 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.