lemlist People Database API
Search the lemlist B2B people and company database, list its filters, and manage saved personas.
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OpenAPI Specification
openapi: 3.2.0
info:
title: Lemlist People database API
version: 1.0.0
description: 'Operations tagged People database across 3 of this provider''s published API definitions: lemlist-openapi-v1-legacy.json, lemlist-openapi-v2.json, lemlist-openapi.yml. Each path carries the servers of the definition it was published in.'
servers:
- url: https://api.lemlist.com/api
tags:
- name: People database
paths:
/database/filters:
parameters: []
get:
summary: Filters
tags:
- People database
parameters:
- name: Content
in: header
required: false
example: application/json
schema:
type: string
responses:
'200':
headers:
Content-Type:
schema:
type: string
example: application/json
description: Success
content:
application/json:
schema:
type: array
items:
type: object
properties:
filterId:
type: string
description:
type: string
mode:
type: array
items:
type: string
type:
type: string
helper:
type: string
example:
- filterId: filterId
description: filterId description
mode:
- leads
- companies
type: text
helper: Use free text search (to fill the in and/or out array)
servers:
- url: https://api.lemlist.com/api
/database/people:
parameters: []
post:
summary: People database
tags:
- People database
parameters:
- name: Content
in: header
required: false
example: application/json
schema:
type: string
responses:
default:
headers:
Content-Type:
schema:
type: string
example: application/json
description: Success
content:
application/json:
schema:
type: object
properties:
results:
type: array
items: {}
total:
type: integer
took:
type: integer
page:
type: integer
size:
type: integer
search:
type: string
limitation:
type: integer
team:
type: string
example:
results: []
total: 18540918
took: 903
page: 1
size: 100
search: lsh_ENeC6oBSdwSArkywL
limitation: 999
team: tea_MtScZ2GexXzHXRdTr
requestBody:
content:
application/json:
schema:
type: object
properties:
filters:
type: array
items:
type: object
properties:
filterId:
type: string
in:
type: array
items:
type: string
out:
type: array
items: {}
page:
type: integer
example:
filters:
- filterId: country
in:
- France
out: []
page: 1
servers:
- url: https://api.lemlist.com/api
/schema/people:
parameters: []
get:
summary: People schema
tags:
- People database
parameters:
- name: Content
in: header
required: false
example: application/json
schema:
type: string
responses:
default:
headers:
Content-Type:
schema:
type: string
example: application/json
description: Success
content:
application/json:
schema:
type: object
properties:
schema:
type: object
properties:
lead_id:
type: integer
canonical_shorthand_name:
type: string
connections_count:
type: integer
country:
type: string
full_name:
type: string
education:
type: array
items:
type: object
properties:
activities_and_societies:
type: string
created:
type: string
format: style
date_from:
type: string
format: utc-millisec
date_to:
type: string
format: utc-millisec
deleted:
type: string
format: utc-millisec
description:
type: string
id:
type: string
format: utc-millisec
last_updated:
type: string
format: style
member_id:
type: string
format: utc-millisec
school_url:
type: string
format: uri
subtitle:
type: string
title:
type: string
experience_count:
type: integer
experiences:
type: array
items:
type: object
properties:
company_id:
type: integer
company_description:
type: string
company_employee_count:
type: integer
company_followers_count:
type: integer
company_founded:
type: integer
company_headquarters_city:
type: string
company_headquarters_country:
type: string
company_industry:
type: string
company_linkedin_url:
type: string
format: uri
company_logo_url:
type: string
format: uri
company_name:
type: string
company_size:
type: string
company_type:
type: string
company_url:
type: string
format: uri
company_website_url:
type: string
format: uri
employees_count_bucket:
type: string
revenue_bucket:
type: string
company_domain:
type: string
employees_count_growth:
type: integer
company_is_hiring:
type: boolean
company_function_array:
type: array
items:
type: string
last_funding_round_at:
type: string
format: date
techno_used_array:
type: array
items:
type: string
business_business_customer:
type: string
format: color
current_exp_bucket:
type: string
created:
type: string
format: style
date_from:
type: string
date_to:
type: string
description:
type: string
duration:
type: string
id:
type: string
format: utc-millisec
last_updated:
type: string
format: style
location:
type: string
member_id:
type: string
format: utc-millisec
order_in_profile:
type: integer
title:
type: string
title_normalized:
type: string
main_in_profile:
type: boolean
interests:
type: array
items:
type: object
properties:
interest:
type: string
interest_id:
type: string
languages:
type: array
items:
type: object
properties:
language:
type: string
proficiency:
type: string
last_updated:
type: string
format: style
lead_industry:
type: string
lead_linkedin_url:
type: string
format: uri
lead_logo_url:
type: string
format: uri
linkedin_short:
type: string
location:
type: string
skills:
type: array
items:
type: object
properties:
skill:
type: string
skill_id:
type: string
summary:
type: string
title:
type: string
lead_quality_score:
type: integer
seniority:
type: string
department:
type: string
connections_count_bucket:
type: string
years_of_exp_bucket:
type: string
current_exp_company_name:
type: string
geopoint:
type: array
items:
type: number
_score:
type: number
_id:
type: string
format: utc-millisec
version:
type: integer
example:
schema:
lead_id: 231488528
canonical_shorthand_name: john-doe-123456718
connections_count: 500
country: United States
full_name: John Doe
education:
- activities_and_societies: AI Research Club, Robotics Team
created: 2024-01-17 06:49:05 UTC
date_from: '2019'
date_to: '2022'
deleted: '0'
description: Focus on Machine Learning and Data Science
id: '2630204628'
last_updated: 2024-01-17 06:49:05 UTC
member_id: '231488528'
school_url: https://university.edu/profile
subtitle: Master of Science in Computer Science
title: Stanford University
experience_count: 3
experiences:
- company_id: 789012
company_description: Leading AI and Machine Learning Solutions Provider
company_employee_count: 5000
company_followers_count: 50000
company_founded: 2010
company_headquarters_city: San Francisco
company_headquarters_country: United States
company_industry: Information Technology
company_linkedin_url: https://linkedin.com/company/techcorp
company_logo_url: https://company.com/logo.png
company_name: TechCorp Inc.
company_size: 1001-5000 employees
company_type: Public Company
company_url: https://linkedin.com/company/techcorp
company_website_url: https://techcorp.com
employees_count_bucket: 1001-5000
revenue_bucket: $50M - $100M
company_domain: techcorp.com
employees_count_growth: 25
company_is_hiring: true
company_function_array:
- Engineering
- Research
- Information Technology
last_funding_round_at: '2023-12-15'
techno_used_array:
- Python
- TensorFlow
- AWS
- Docker
business_business_customer: B2B
current_exp_bucket: 1 to 3 years
created: 2024-01-17 04:41:50 UTC
date_from: Jan 2022
date_to: Present
description: Leading AI initiatives and machine learning projects
duration: 2 years 1 month
id: '2194433831662'
last_updated: 2024-01-17 04:41:50 UTC
location: San Francisco Bay Area
member_id: '231488528'
order_in_profile: 1
title: Senior Machine Learning Engineer
title_normalized: Senior Machine Learning Engineer
main_in_profile: true
interests:
- interest: Artificial Intelligence
interest_id: ai-123
- interest: Machine Learning
interest_id: ml-456
languages:
- language: English
proficiency: native or bilingual proficiency
- language: Spanish
proficiency: professional working proficiency
last_updated: 2024-01-17 06:49:05 UTC
lead_industry: Technology
lead_linkedin_url: https://linkedin.com/in/john-doe-123456789
lead_logo_url: https://media.linkedin.com/photo.jpg
linkedin_short: john-doe-123456789
location: San Francisco Bay Area, California
skills:
- skill: Machine Learning
skill_id: ml-789
- skill: Python Programming
skill_id: python-101
summary: Senior Machine Learning Engineer with 8+ years of experience in AI and data science. Focused on developing scalable ML solutions for enterprise clients.
title: Senior Machine Learning Engineer at TechCorp Inc.
lead_quality_score: 85
seniority: Senior
department: Engineering
connections_count_bucket: 500+
years_of_exp_bucket: 5-10 years
current_exp_company_name: TechCorp Inc.
geopoint:
- -122.4194155
- 37.7749295
_score: 8.6079
_id: '231488528'
version: 18
requestBody:
content:
application/json:
schema:
type: object
properties:
filters:
type: array
items:
type: object
properties:
filterId:
type: string
in:
type: array
items:
type: string
out:
type: array
items: {}
page:
type: integer
example:
filters:
- filterId: country
in:
- France
out: []
page: 1
servers:
- url: https://api.lemlist.com/api
/database/companies:
parameters: []
post:
summary: Companies database
tags:
- People database
parameters:
- name: Content
in: header
required: false
example: application/json
schema:
type: string
responses:
default:
headers:
Content-Type:
schema:
type: string
example: application/json
description: Success
content:
application/json:
schema:
type: object
properties:
results:
type: array
items: {}
total:
type: integer
took:
type: integer
page:
type: integer
size:
type: integer
search:
type: string
limitation:
type: integer
team:
type: string
example:
results: []
total: 18540918
took: 903
page: 1
size: 100
search: lsh_ENeC6oBSdwSArkywL
limitation: 999
team: tea_MtScZ2GexXzHXRdTr
requestBody:
content:
application/json:
schema:
type: object
properties:
filters:
type: array
items:
type: object
properties:
filterId:
type: string
in:
type: array
items:
type: string
out:
type: array
items: {}
page:
type: integer
example:
filters:
- filterId: currentCompanyTechnologies
in:
- Postman
out: []
page: 1
servers:
- url: https://api.lemlist.com/api
/schema/companies:
parameters: []
get:
summary: Companies schema
tags:
- People database
parameters:
- name: Content
in: header
required: false
example: application/json
schema:
type: string
responses:
default:
headers:
Content-Type:
schema:
type: string
example: application/json
description: Success
content:
application/json:
schema:
type: object
properties:
schema:
type: object
properties:
company_id:
type: integer
company_website_url:
type: string
format: uri
company_name:
type: string
company_linkedin_url:
type: string
format: uri
last_updated:
type: string
format: style
company_headquarters_city:
type: string
company_headquarters_country:
type: string
company_logo_url:
type: string
format: uri
company_description:
type: string
company_employee_count:
type: integer
company_type:
type: string
company_founded:
type: integer
company_size:
type: string
company_followers_count:
type: integer
employees_count_bucket:
type: string
revenue_bucket:
type: string
company_domain:
type: string
employees_count_growth:
type: integer
company_is_hiring:
type: boolean
company_function_array:
type: array
items:
type: string
last_funding_round_at:
type: string
format: date
techno_used_array:
type: array
items:
type: string
business_business_customer:
type: string
format: color
company_quality_score:
type: integer
company_industry:
type: string
company_sub_industry:
type: string
company_location:
type: string
version:
type: integer
example:
schema:
company_id: 7842391
company_website_url: https://www.innovatetech.io
company_name: InnovateTech Solutions
company_linkedin_url: https://www.linkedin.com/company/innovatetech-solutions
last_updated: 2024-03-15 09:30:22 UTC
company_headquarters_city: Austin
company_headquarters_country: United States
company_logo_url: https://media.linkedin.com/companies/innovatetech/logo_200_200.png
company_description: InnovateTech Solutions is a leading provider of AI-powered enterprise software solutions. We specialize in developing cutting-edge machine learning applications that help businesses automate their workflows and make data-driven decisions. Our team of experts combines deep technical knowledge with industry expertise to deliver transformative solutions.
company_employee_count: 245
company_type: Privately Held
company_founded: 2018
company_size: 201-500 employees
company_followers_count: 15000
employees_count_bucket: 201-500
revenue_bucket: $50M - $100M
company_domain: innovatetech.io
employees_count_growth: 35
company_is_hiring: true
company_function_array:
- Software Development
- Artificial Intelligence
- Enterprise Solutions
- Cloud Computing
last_funding_round_at: '2023-11-15'
techno_used_array:
- Python
- TensorFlow
- AWS
- Docker
- Kubernetes
- React
- Node.js
- PostgreSQL
business_business_customer: B2B
company_quality_score: 85
company_industry: Information Technology
company_sub_industry: Enterprise Software
company_location: Austin, Texas, United States
version: 2
requestBody:
content:
application/json:
schema:
type: object
properties:
filters:
type: array
items:
type: object
properties:
filterId:
type: string
in:
type: array
items:
type: string
out:
type: array
items: {}
page:
type: integer
example:
filters:
- filterId: country
in:
- France
out: []
page: 1
servers:
- url: https://api.lemlist.com/api
/database/personas:
get:
summary: List Personas
description: 'Lists the personas saved by your team. A persona is a named, reusable set of People Database filters; its id can then be referenced elsewhere in the API, for example through the `persona` filter of a Signal Agent.
Personas are team-shared: every member sees the same list. Results are sorted by creation date, most recent first, and capped at 200. The auto-generated persona lemlist derives from your AI business context is never returned; only the personas your team created are.
This endpoint is in closed beta and answers `403` unless the beta is enabled for your team.'
operationId: listPersonas
tags:
- People database
parameters:
- name: mode
in: query
required: false
description: Restrict the list to personas of one search mode. Omit to return every persona of the team.
schema:
type: string
enum:
- leads
- companies
example: leads
responses:
'200':
description: Success
content:
application/json:
schema:
$ref: '#/components/schemas/PersonaListResponse'
example:
data:
- _id: pdp_ExAmPlE1234567890a
name: SaaS founders
mode: leads
filters:
- filterId: currentTitle
in:
- Founder
out: []
- filterId: country
in:
- France
out: []
createdAt: '2026-07-31T09:12:00.000Z'
updatedAt: '2026-07-31T09:12:00.000Z'
'400':
description: Validation error - invalid query parameters
content:
application/json:
schema:
$ref: '#/components/schemas/PersonaError'
example:
error: Parameter "mode" must be "leads" or "companies"; user personas currently accept "leads" only
code: PEOPLE_DATABASE_PERSONA_API_INVALID_MODE
'401':
description: Unauthorized - invalid or missing API key
content:
application/json:
schema:
$ref: '#/components/schemas/PersonaError'
example:
error: Route unauthorized
code: ROUTE_UNAUTHORIZED
'403':
description: The personas beta is not enabled for your team
content:
application/json:
schema:
$ref: '#/components/schemas/PersonaError'
example:
error: Beta is not enabled
code: BETA_NOT_ENABLED
'500':
description: Internal server error
content:
application/json:
schema:
$ref: '#/components/schemas/PersonaError'
example:
error: Internal error
code: INTERNAL_ERROR
security:
- basicAuth: []
post:
summary: Create Persona
description: 'Creates a persona for your team from a name and a set of People Database filters.
Use [Get Database Filters](/api-reference/endpoints/people-database/get-database-filters) to discover the valid `filterId` values. Filters carry no `type` property: it is derived from `filterId` server-side. Filters that require a plan your team does not have are dropped silently, so the persona is stored with the subset your plan allows.
Only the created id is returned. The stored `name` and `filters` are sanitized and plan-gated server-side, so echoing the request payload back would misreport what was persisted; call [List Personas](/api-reference/endpoints/people-database/list-personas) to read the stored persona.
This endpoint is in closed beta and answers `403` unless the beta is enabled for your team.'
operationId: createPersona
tags:
- People database
requestBody:
required: true
content:
application/json:
schema:
type: object
required:
- name
- filters
- mode
properties:
name:
type: string
minLength: 1
description: Display name. Non-empty, and unique within your team.
example: SaaS founders
filters:
type: array
description: People Database filters defining the persona
items:
$ref: '#/components/schemas/PersonaFilter'
mode:
type: string
descrip
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# Full source: https://raw.githubusercontent.com/api-evangelist/lemlist/refs/heads/main/openapi/lemlist-people-database-api-openapi.yml