Gender API
Analytics & DataInfer the gender most commonly associated with a personal name through the Gender API Unified API. Agents split a full name, look up a first name, and personalize salutations with a stated confidence level.
What This Integration Enables
Gender API looks a first name up in a name database and returns the gender label most commonly recorded against it, a probability between 0 and 1, and the number of database samples the label came from. Read that sentence carefully, because it is the whole product. This is a statistical statement about a name string. It is not a fact about a person, and no amount of enrichment turns it into one. When a name is not in the database, result_found comes back false and the gender comes back as "unknown", which is the API being honest rather than the API failing.
Used for what it is good for, it earns its place. The legitimate jobs are addressing people correctly and understanding a population in aggregate: picking a salutation that is not awkward, choosing the right grammatical form in a language where adjectives inflect, and measuring the composition of an audience or a survey panel at the group level. Split Full Name And Infer Gender also does real, unglamorous data hygiene by separating a single free-text name field into first and last name. Get Name Country Of Origin returns the countries a name is most associated with alongside its language of origin and meaning, which is useful for localization.
What it must not be used for is deciding anything about the individual behind the name. An inferred gender, origin or ethnicity is not a basis for a hiring, lending, pricing, insurance or eligibility decision, and in many jurisdictions using it that way is unlawful. FlowRunner's design position follows from that rather than sitting beside it: the confidence score is load-bearing, and low confidence routes to a person. Accuracy improves when a lookup is localised with a country code, a browser locale such as en_US, or the visitor's address, with country taking precedence, then locale, then IP.
Without FlowRunner
With FlowRunner
Use Case Scenarios
Normalising an imported contact list
A list arrives from an event with 4,000 rows and a single Name column. The agent runs Split Full Name And Infer Gender across the batch. The immediate win is structural: first_name and last_name come back separated, which is what makes every downstream template work at all. The gender label rides along with a probability and a sample count. Records above the threshold get a salutation assigned; records below it get the neutral variant and no gender field written. The parsed names are written back to HubSpot regardless, because the parsing is reliable in a way the inference is not.
Enriching a list captured as email addresses only
A newsletter signup captured nothing but the address. Infer Gender From Email Address extracts whatever personal name is embedded in it and returns the detected first and last name plus the inference. Plenty of addresses yield nothing usable and come back with result_found false, and the agent leaves those rows entirely alone rather than filling them with a default. The ones that do resolve get a first name the welcome email can actually use, which is the point. The greeting is the outcome, not a profile.
Measuring the composition of a survey panel
A research team wants to know the gender balance of a completed survey panel to report alongside the results. The agent runs Infer Gender For Query Batch over the panel, mixing first names and email addresses freely across entries with a reference id echoed back per row, then aggregates immediately to a distribution with the confidence spread reported next to it. The number that goes in the report is a group-level estimate derived from names, and the report says so. No per-person label is retained after the aggregate is computed.
Human-in-Loop Highlight
The gate is the write-back, and it exists because writing an inferred value into a CRM field launders a guess into what looks like a fact. Once a Gender column sits on a contact record, every colleague who reads that record afterwards treats it as something the person told you, and every downstream template consumes it without ever seeing the 0.58 probability that produced it. The agent will not do that quietly. It parses and writes the name fields on its own authority, because Split Full Name And Infer Gender is reliable at splitting. Then it stops on the inference and asks the CRM owner in Slack: "1,180 of 4,000 imported contacts returned a gender probability below 0.85, and 340 returned result_found false. Write the field for these rows, leave them blank and use the neutral salutation, or write it with the probability stored alongside it?" The default the agent proposes is blank, because a missing field is honest and a confident-looking wrong one is not. This is human-in-the-loop applied where it belongs, at the moment uncertainty is about to be erased.
Agent Capabilities
6 actionsGender Inference
4- Infer Gender From First Name Looks a first name up in the Gender API name database and returns the gender label most commonly recorded for it, a probability between 0 and 1, and the number of database samples behind the label. This is a statistical inference about the name string, not a verified fact about a person, and result_found is false with gender "unknown" when the name is not in the database. Localising with a country code, a locale such as en_US, or the visitor's address improves accuracy, with country taking precedence, then locale, then IP. Costs 1 credit.
- Split Full Name And Infer Gender Splits a combined first-and-last-name string into first_name and last_name and, in the same call, returns the gender label most commonly recorded for the extracted first name with its probability and sample count. Used to normalise a single free-text name field captured on a form or imported from a CRM. The split is the dependable half; the gender remains a statistical inference about the name. Maximum 100 characters, costs 1 credit.
- Infer Gender From Email Address Extracts the personal name embedded in an email address, returns the detected first_name and last_name, and infers the gender label for that first name with a probability and sample count. Used to enrich signup or newsletter lists where only an address was captured. Both the extraction and the label are statistical inferences, and result_found is false when no usable name can be extracted. Maximum 100 characters, costs 1 credit.
- Infer Gender For Query Batch Resolves many lookups in one call, mixing first names, full names and email addresses freely across entries, and returns one result per entry in submitted order. Each entry may carry its own country, locale or IP localisation and a reference id that is echoed back, which is what makes it practical for enriching an imported list. Every result carries its own probability and sample count. Each entry costs 1 credit, and the lookups allowed per request depend on the plan, with free keys limited to 3.
Name Origin
1- Get Name Country Of Origin Returns the countries a name is most likely to originate from, ranked by probability across up to the top 25 countries with their continental and statistical regions, plus the language of origin, a short description of the name's meaning, and its distribution across ethnic groups. Accepts a first name, a full name or an email address. Every value describes the distribution of the name in the provider's database, not the nationality or ethnicity of any individual, and is appropriate for localization and aggregate analysis rather than for decisions about a person. Costs 2 credits.
Account
1- Get Account Statistics Returns the current state of the connected account: remaining request credits, whether the plan limit has been reached, and the credits consumed last month. This call is free and consumes no credits, so it is safe to run before a large batch. Name lookups cost 1 credit each and country-of-origin lookups cost 2.
Frequently Asked Questions
What can FlowRunner do with Gender API?
FlowRunner agents can run Infer Gender From First Name, Split Full Name And Infer Gender, and Infer Gender From Email Address in Gender API, plus 3 more actions.
Does connecting Gender API to FlowRunner require OAuth?
No. Gender API connects to FlowRunner with an API key, no OAuth flow required.
Can Gender API trigger a FlowRunner workflow automatically?
Gender API doesn't currently expose triggers in FlowRunner. It connects as an action step inside workflows started by another trigger.
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