Trusted by leading organizations
Integrate age prediction directly into your workflows and perform efficient inference on big datasets with our simple APIs built for high volumes. Get started quickly with community libraries for any programming language.
Our name parsing algorithm allows you to pass full names to our API's.
We support diacritics from any language as well as non-latin alphabets.
Our dataset covers the whole planet and we support scoping your requests to specific countries.
Looking to enrich your data with demographic insights? Our CSV tool allows you to upload your data and check gender, age and nationality predicted in minutes.
Using CSV processing is a quick way to gain insights into your users, audience, prospects and customers by analysing their demographic composition.
Upload CSVWith our collection of services we offer prediction of gender, age and nationality from a name.
genderize.io
Classify gender from names
agify.io
Estimate age from names
nationalize.io
Predict nationality from names
For more than 12 years we've been collecting and processing data. Today we base our results on more than 1 billion people and have processed billions of requests.
Read about our dataAge estimation has applications across many different fields and industries. The ability to enhance existing datasets with demographic data can unlock new possibilities in both commercial and academic projects.
Explore casesRun age estimation on your customers, audience, or user datasets and gain insights into your market. Enhancing your customer profiles with demographic information can improve product development, content strategies, marketing, and promotional activities.
Understand the age distribution in big corpora to analyze diversity and potential biases. Age estimation of authors, characters, or public figures mentioned in texts can help quantify and analyze biases and disparities in media and literature.
Analyse the audience of your brand, channel or media. Understand the demographic makeup of your consumers to unlock insights and improve content development strategies.
Users of our services have open sourced amazing libraries for our API's, making it easy to integrate our name checking technology into any stack. You'll find libraries for nearly every programming language.
Python client for the Genderize.io web service.
R package for gender predictions
Laravel 5 client for the Genderize.io API
A simple python library to take first names and return their gender using the genderize.io API.
php lib for handling genderize.io
Guess the gender of names with the help of the genderize.io.
Simple Java extension to know the gender of a given first name. It consumes the http://genderize.io API.
Detect gender from name using genderize.io API
Genderize.io Ruby SDK.
Laravel 8+ client for the Genderize.io API
A client wrapper for the genderize.io API
R wrapper for the genderize.io, agify.io & nationalize.io APIs
A small Gem that makes it possible to determine gender from a name via the Genderize.io service.
Client for Genderize.io web service.
A golang library for agify.io API
A client for the genderize.io API
A golang module for calling nationalize.io
genderize is a simple client for genderize.io, a gender prediction API
Create an account in minutes to claim your API key and have unrestricted access.
Register an accountThe API and CSV tool is free for up to 100 names/day. No sign up or API key needed, so go ahead and try it out.
We offer multiple tiers of usage. Cancellation at any time and no retention period.
See pricingJournalists, academics, and developers have used our APIs to analyze millions of records. Here are some of their stories.
Becky Gardiner, Mahana Mansfield, Ian Anderson, Josh Holder, Daan Louter, and Monica Ulmanu · 2016
Analyzed 70 million comments left on The Guardian since 2006. Of the 10 most-abused writers, 8 were women and the 2 men were Black. Led to moderation changes.
Miguel Landa-Blanco and Christian R. Mejia · 2023
Analyzed 10,558 articles in NEJM, JAMA, BMJ, Lancet, and Nature Medicine (2010–2019). Women: 34.5% first authors, 24.8% senior authors.
Alex Holmes and Sally Hardy · 2019
Analyzed Regional Studies journal submissions 2011–2016 using Genderize.io. Men submitted 67% of papers and had a 31% acceptance rate; women submitted 33% with a 24% acceptance rate.
Christopher Ingraham · 2014
Analyzed gender of directors for the top 400 films by box office over five years. Women directed just 14% in 2013 — and only 2 of the top 100.
Names go through cycles of popularity resulting in a correlation between first names and birth years. With a dataset of ~1 billion people, Agify gives statistical probabilities on the likely age of a person based on their name. Scoping to a specific country typically improves accuracy, since naming trends vary across cultures and regions.
Naming conventions can be different across countries and cultures. Our APIs support scoping a prediction to a specific country using the
country_id
parameter (ISO 3166-1 alpha-2 code), which will in many cases make the prediction significantly more accurate. For example, "Kim" is predominantly male in Denmark but predominantly female in the United States.
Yes. You can enrich CRM data with gender, age, and nationality predictions through our official no-code apps for Zapier, Make, and Pipedream . These integrations let you automatically process new contacts as they're added. For more custom setups, the API is straightforward to call from any CRM with webhook or API support.
You can reach us at info@genderize.io for any questions. We're happy to help you get the most out of our APIs, whether you need guidance on integration, data coverage, or choosing the right plan.