NameAPI is a web API
to handle people's names
in your software.



Expanded NameAPI Database for Company Legal Forms

We've expanded our NameAPI database to include a comprehensive list of company legal forms from...


Software Version 10.3.0 Deployed

We are pleased to announce the deployment of Software Version 10.3.0, bringing significant...


Sinhala Names: A Window into Sri Lanka’s Cultural Identity

Sri Lanka, an island nation nestled in the Indian Ocean, captivates with its diverse landscapes,...


Enhanced NameAPI Database

We've updated our NameAPI database to better handle names that include professions. We have added...


Bosnian names: Echoes of Diversity and Heritage

Bosnia and Herzegovina stands out in Europe for its remarkable diversity, being a country where...


Name Genderizer

Attempts to detect the person's gender based on the inputs, especially the person's name.
See also the Swagger specification.
application/json (you must set the content-type as http header)
We have integrated Swagger directly into our API.



See Context.
  "context" : {
     "priority" : "REALTIME",
     "properties" : [ ]
  "inputPerson" : {
    "type" : "NaturalInputPerson",
    "personName" : {
      "nameFields" : [ {
        "string" : "Andrea",
        "fieldType" : "GIVENNAME"
      }, {
        "string" : "Bocelli",
        "fieldType" : "SURNAME"
      } ]
    "gender" : "UNKNOWN"



Possible values:

The person is clearly 'male'.

The person is clearly 'female'.

Can be either male or female. See malePercent.

No gender could be computed, but better intelligence should be able to tell the gender. An example is a name input of which we have never heard before.

From the given data it is or seems impossible to tell the gender.
For example all terms are gender-inapplicable, or there are no names at all. Thus this differs from NEUTRAL where something is clearly known to be neutral.

There are conflicting genders in the given data.
Example: "Mr Daniela Miller" (salutation vs. given name).
The input data must be manually reviewed. It is impossible and useless to make a guess (garbage in would only cause garbage out).

If neutral (otherwise null) then this may be specified (but does not have to be), 0-1, the remaining % are for female.
0-1 where 1 is the best.
  "gender" : "MALE",
  "confidence" : 0.9111111111111111