Find answers to our most frequent questions

Genderize is an API that predicts the gender of a person based on their first name. It uses a dataset of around a billion records to return a statistical probability — for example, that "Anna" is 97% likely to be female. You can try it instantly in your browser at api.genderize.io?name=anna.

All three APIs share one ~1 billion-row dataset and one API key. A single subscription covers gender, age, and nationality predictions.

Our APIs are used by academic researchers, data scientists, marketers, HR teams, journalists, and developers worldwide. Notable users include The Guardian, MIT, Columbia University, Yale University, Uber, Shopify, Nature, and The Washington Post. Genderize.io alone has been cited in over 1,400 academic papers.

Genderize returns the predicted gender, a probability score (0–1), and a row count — see the API reference for the full response shape. Names used across both genders, like "Kim" or "Alex," return probabilities near 0.5.

Yes — we recommend it whenever you have the data. Pass the country_id parameter (ISO 3166-1 alpha-2) to scope predictions to a specific country .

We recommend sending the first name only, as that gives the most accurate results for gender and age prediction. However, if you only have a full name, the API will attempt to parse out the first name automatically.

Yes. You can send up to 10 names per request using array syntax: name[]=anna&name[]=john&name[]=kim. Each name counts individually toward your usage limit.

The API tries the name directly, then with diacritics removed, then parses a first or last name out of a full name (also retried without diacritics). If all attempts miss, prediction fields return null.

Our dataset consists of around a billion data rows covering 249 countries and territories. You can explore the full coverage breakdown on our Our Data page.

Our data is collected from publicly available sources across the web. We have been collecting and processing name-based demographic data for over 12 years.

Gender prediction is based on statistical probability. If a name returns a probability of 0.92 for female, it means 92% of the people with that name in our dataset are female. On an unbiased sample, the prediction will be correct at that same rate.

Names like "Alex," "Jordan," or "Robin" are used by both genders. For these names, the probability score will be closer to 0.5, reflecting the genuine split in our dataset.

Extensively — over 1,400 scholarly articles across sociology, computer science, economics, medicine, and media studies. See our case studies for examples.

Yes. You can enrich CRM data with gender, age, and nationality predictions through our official no-code integrations : n8n and Pipedream work with all three APIs, and Zapier and Make are available for Genderize. For LLM-driven CRMs, you can also connect via our MCP server . For more custom setups, the API is straightforward to call from any CRM with webhook or API support.

Yes. We offer a Spreadsheet tool that lets you upload a file and get predictions added as new columns. We also have official no-code integrations : n8n and Pipedream for all three APIs, plus Zapier and Make for Genderize. For agent-based workflows, each service exposes an MCP server .

Yes. Each service exposes a hosted MCP server that works with Claude, Cursor, ChatGPT, and any other MCP-compatible client.

The easiest way is through our official no-code apps for Zapier, Make, n8n, and Pipedream . These let you automatically classify customers by gender as they enter your system. For a more custom solution, you can call the Genderize API directly — it's a single HTTP call per name with no SDK required.

Yes. Our Spreadsheet tool lets you upload a file with a name column and get a gender column added automatically. You can also set up automated spreadsheets that update gender when new rows are added — see our guide on checking gender in Google Sheets using Zapier .

Genderize returns binary (male/female) predictions based on dataset distribution. If non-binary sensitivity matters, use the probability score — names near 0.5 are essentially gender-neutral — and treat them accordingly.

Report which API and parameters you used, acknowledge that name-based inference is a statistical tendency rather than individual identity, and be transparent about how uncertain predictions are handled.

Context-dependent. Name-based classification works for large-scale studies where individual-level data isn't available. Be transparent about limitations and align with your institution's ethics guidelines.

Gender prediction is binary and won't capture non-binary identities. Some names are genuinely ambiguous and will yield low-confidence results. Predictions reflect population statistics, not individual certainty — use the probability and count fields to assess confidence.

Yes. Sign up for 2,500 names/month free — no credit card required. Paid subscriptions start at $20/month.

One API key covers all three APIs (Genderize, Agify, Nationalize). Plans range from 25,000 names/month ($20) to 25,000,000/month ($540). Annual billing saves two months.

We count names, not API calls. If you send a batch of 100 names in a single request, that counts as 100 names against your monthly limit. A CSV upload with 10,000 rows counts as 10,000 names. One name in, one name counted — however you send it.

Requests above your limit return a 429 Too Many Requests response until your next billing cycle starts. We never charge overage fees. Upgrade takes effect immediately.

Yes. Upgrades take effect immediately and we prorate the difference. Downgrades take effect at the start of your next billing cycle, so you keep the higher limit until then.

No. Limits reset at the start of each billing cycle.

Yearly billing costs the same as 10 months of monthly billing — you get two months free. You're charged once per year and your limit resets monthly as usual.

No. Your subscription stays at the price you signed up at for as long as you remain subscribed. If we raise prices, only new customers pay the new rate. Cancel and resubscribe later and you'll be on whatever the current pricing is at that point.

Yes. Cancel from your dashboard in one click. You keep access until the end of your current billing period, and we don't ask why or try to talk you out of it.

All major credit and debit cards, plus PayPal, processed through Stripe. For yearly Enterprise plans we also support invoicing and bank transfer.

We use Stripe as our payment provider. Your credit card details and billing information are stored with Stripe and never touch our systems.

Go to your account page and click "Billing dashboard" under the Billing management section. This takes you to Stripe's billing portal where you can update your details.

We cannot manually trigger a charge. Stripe will retry up to four times within two weeks. As long as a working payment method is on file before the last attempt, you'll be fine.

Sign up for a free account — your API key shows up in your dashboard immediately. Upgrade from your dashboard whenever you need higher limits.

There is no rate limiting — you can make requests as fast as you need. All plans (free and paid) have a monthly name allowance that resets each billing cycle.

Email info@genderize.io for any questions.

We don't store the names you submit via the API — they're discarded immediately, not written to any database or log. CSV uploads are processed in memory; the results file is deleted after you download it or after 24 hours. We don't log IP addresses.

Demografix ApS is a Danish company, directly subject to the GDPR. We practice data minimization by design: we don't store the names you submit, we don't log IP addresses, and our website analytics are cookieless. For full details, see our GDPR & Data Protection page and our Privacy Policy .

Yes. Our Data Processing Agreement is available and applies automatically through our Terms of Service. If your organization requires a countersigned copy, contact us at info@genderize.io .

Our infrastructure is hosted by DigitalOcean in the United States. For details on international data transfers and the safeguards in place, see our GDPR & Data Protection page.