Tools

What the model sees. Descriptions are written for the model, so they say exactly what each filter does.

describe_catalog#

Every filter with its type and allowed values, live facts about the data (people, how many have an email, phone or LinkedIn, top countries), whether contact data is included for your account, and your usage. Free. Models should call it first.

search_people#

Find people. At least one filter is required; filters combine with AND, values inside one filter with OR. Returns {people, next_cursor, contact_fields_included}.

Arguments
titlestring[]
Job title keywords, OR'd: a person matches if their title contains ANY of them (case-insensitive), e.g. ['vp sales', 'head of sales'].
title_excludestring[]
Drop people whose title contains ANY of these, e.g. ['assistant', 'intern'].
title_whole_wordsboolean
Match title and title_exclude as whole words: 'cto' finds 'CTO' but not 'Director'. Short single-word values (4 letters or fewer) always match as whole words.
companystring[]
Company name contains ANY of these (case-insensitive), e.g. ['stripe'].
company_exactboolean
Match company names exactly instead of 'contains', so 'meta' does not also find 'Metallica'.
exclude_companystring[]
Drop people at companies whose name contains ANY of these.
departmentstring[]
Job family, any of the listed values.
Executive & General ManagementSalesOperations & LogisticsFinance & AccountingSoftware EngineeringHealthcare & NursingEngineering (Non-Software)Marketing & CommunicationsEducation & TrainingIT & InfrastructureAdministrativeRetail & HospitalityManufacturing & Skilled TradesPeople & HRScience & ResearchCustomer Success & SupportLegal & ComplianceProduct & DesignData & AICybersecurityOther
levelstring[]
Seniority, any of the listed values. Decision makers are Owner / Founder, C-suite, VP and Director / Head.
Owner / FounderC-suiteVPDirector / HeadManagerSeniorStaffIntern / Student
industrystring[]
The company's industry contains ANY of these, e.g. ['software', 'banking'].
company_sizestring[]
Company headcount bucket(s).
1-45-1920-99100-249250-499500-9991,000-4,9995,000-9,99910,000+
revenuestring[]
The company's annual revenue range, any of the listed values. Companies with unknown revenue are excluded.
<$1M$1-10M$10-50M$50-100M$100-500M$500M-1B$1B+
countriesstring[]
ISO-3166 alpha-2 country codes, e.g. ['US', 'CA'].
statesstring[]
US state, Canadian province or Australian state codes, e.g. ['CA', 'TX']. Other countries have no clean region data. Combine with countries to avoid clashes (CA is California and Canada).
citystring[]
City name contains ANY of these, e.g. ['austin'].
has_emailboolean
Only people with an email on file.
has_phoneboolean
Only people with a phone number on file.
has_linkedinboolean
Only people with a LinkedIn profile on file.
has_company_phoneboolean
Only people whose company has a main phone number on file.
limitinteger
People per page, 1-100 (default 25).
cursorstring
Pass the previous response's next_cursor to get the next page.

count_people#

How many people match, and how many of them have an email, phone and LinkedIn on file. Same filters as search_people, without paging. Add group_by to get the top 25 values of a field instead, for example which companies employ the most matching people.

Extra argument
group_bystring
Break the count down by this field.
departmentlevelindustrycountrystatecompany_sizerevenuecompanytitle

get_people#

Arguments
idsstring[]required
Up to 100 ids from search_people.

Several people by id, in the order given. Unknown ids come back in missing.