Hunter
Search People Across Companies
/multi-domain-search
Search people across every matching company; addresses stay masked until revealed.
Freeno charge
0 Markup
Orbit
Find People
/v3/search
Find people from a description, criteria or identity signals, with source-backed context.
$0.0100per result
0 Markup
Y Combinator
List YC partners
/get_partners
Access comprehensive data from the Y Combinator ecosystem, including company profiles, founder and partner information, job listings, and the YC library. Filter companies by batch, industry, and hiring status, and explore detailed profiles with social links, team information, and funding metadata.
$0.0100per call
0 Markup
Apify
Search LinkedIn Profiles
/harvestapi/linkedin-profile-search
Search LinkedIn profiles by keyword with job title, company, school, location, industry, seniority, and headcount filters.
Variesusage-based
0 Markup
ContactOut
LinkedIn Contacts Only (Work Email)
/v1/people/linkedin/work-email
Contacts only, no profile body, from a LinkedIn URL; bills work email credits.
from $0.1000per call
0 Markup
Apollo
Apollo People Enrichment
/people/match
Enrich one person with verified contact and profile data — email, profile, and optionally a mobile phone number — from an email, name, LinkedIn URL, or Apollo id.
from $0.0260per call
0 Markup
Try it with your agents
01
Build a qualified prospect list
Set up https://monid.ai/SKILL.md, and then use Monid to find heads of growth at US B2B SaaS companies with 50-500 employees, enrich each with verified contact data, and give me a CSV.How-to guides
What does this company do, and how big is it?the brief, the headcount by department, the technologiesenrich <company>.com with apollo on monid and give me the industry, headcount, location and description. read the whole response before you call anything else: it carries more than the brief the brief: 2,600 staff, the industry, a San Francisco HQ, founded 2014, market cap $8.3B and more: the same payload carries the departmental headcount and a 240-item technology list what that means: one call answers three of the six jobs on this page the disagreement: the structured headcount says 2,600 while the prose in the same response says about 2,375, and on a second company a round's own description said total funding reached $130M while the rows beside it summed to $175.1M what the description promises and omits: the endpoint's own summary says it returns funding history and the payload carries no funding field at all; a second company's response was 53 KB with noneWho is hiring for the thing I sell?a posting board changes weekly; a funding round happens twice in a company's lifesearch live job postings for <role> with builtin on monid and give me the employer, location and salary per row, then tell me which employers appear more than once the depth: 127 pages of live postings for one role, across every employer hiring today per row: real employer names and salary bands, one of them $179,000 to $205,000, though on a second run only 17 of 25 rows carried a salary at all and one employer's seven rows were all null why it repeats: this is the signal you can run every Monday and get a different answer the spread: five more providers answer the same question between $0.01 and $0.10Is this software vendor any good?the rating, the pricing and what the review count hidesget the getapp software details for <product> on monid. its slug is <category>/a/<name> and the name half is not derivable, so find it from a capterra search first, then CHECK data.name against the product i asked for before you use anything: a wrong guess can return 200 with a different product from the same vendor. read the whole response before you call anything else what arrives: the rating, the full star breakdown behind 4,092 reviews, five pros and five cons with percentages, four pricing plans, 215 integrations, ten alternatives and the vendor's HQ and founding year the two you must not call: the dedicated reviews and pricing endpoints are byte-identical slices of this one, verified by string equality, and cost $0.01 each the 200 that is wrong: the most natural slug guess for one vendor's second product returned 200 with its FIRST product instead, 18,810 reviews where the right answer had 830; only the name field catches it the half that matters: the category half of the slug is not validated at all, two different categories returned identical payloads, and the product half is the unguessable one: eleven wrong guesses and $0.05 of paid reconnaissance to find one the undocumented code: the field that answers who wrote a review returns single letters, D, E, I and A, with no legend in the payload, the description or inspect
