Pretrained text classifier

Identify name format with one API call.

A pretrained name format classifier that sorts text into one of 10 categories — the appropriate name format for the given input.. Use the name format API immediately, no training required, then adapt it to your own data when you need more.

Pretrained · Nyckel-trained 10 labels out of the box Text input

Try the name format classifier

Drop in some text and get the prediction back. No signup, no setup.

What this name format classifier recognizes

A sample of the 10 labels this pretrained classifier chooses between.

First Last
First Last Suffix
First Middle Last
First Name Last Name
Initials Last Name
Last First Middle
Last Name First Name
Last Name Initials
Last Name Professional Title
Professional Title First Last

Need a label that isn't here? Clone the classifier into your Nyckel console and edit the label set to fit your data.

Call the name format API

Get your own copy of this classifier behind your own endpoint — callable from any HTTP client:

API quick start
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": "The text you want to classify"}'

Example response

{
  "labelName": "First Last",
  "labelId": "label_...",
  "confidence": 0.92
}

Under the hood

Model type
Nyckel-trained

Trained on a Nyckel-curated dataset covering 10 name format categories, served on Nyckel's own infrastructure — your text snippet stays on Nyckel.

Input
Text

Send raw text to the invoke endpoint; the response is a label with a confidence score.

Make it yours
Adaptable

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.

More than a demo: this page is one of thousands of pretrained functions on Nyckel, an ML classification platform. You can invoke classifiers by API, review predictions, correct labels, collect samples from production traffic, and promote any pretrained function to a private custom model — without changing your integration.

Where teams use name format classification

Customer Support Ticket Sorting

Automatically classify incoming customer support tickets based on their urgency, type, or department. This allows support teams to prioritize and route issues more effectively, leading to faster response times and improved customer satisfaction.

Email Filtering for Marketing Campaigns

Identify and classify email responses from customers into relevant categories such as inquiries, complaints, or feedback. This helps marketing teams analyze customer sentiment and tailor their campaigns accordingly to enhance engagement.

Social Media Post Monitoring

Analyze and classify social media mentions of a brand to determine their sentiment and relevance. By identifying false or misleading mentions, businesses can swiftly address reputational risks and engage positively with their audience.

Resume Screening for Job Applications

Automate the initial screening of job applications by classifying resumes based on qualifications, experience, and fit for the role. This significantly reduces the time and effort spent by HR teams in the recruitment process.

Fraud Detection in Financial Transactions

Classify financial transactions to identify patterns and detect potentially fraudulent activities. By flagging suspicious transactions based on historical data, businesses can mitigate risks and protect customer assets.

Product Review Analysis

Automatically classify product reviews to identify positive, negative, or neutral sentiments. This enables companies to better understand customer feedback and make improvements to their products or services based on real-time data.

Content Moderation for Online Platforms

Use classification to identify and filter out false, misleading, or harmful content posted by users. This helps maintain a safe and trustworthy environment on online platforms, ensuring compliance with community guidelines and legal standards.

Common questions

What's the difference between a zero-shot and a Nyckel-trained classifier?

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.

How do I know whether this will work for my application?

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.

What happens when it makes a mistake?

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.

Do I need training data to get started?

No. This name format 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.

What does it cost to try?

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.

Ready to classify name format at scale?

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.