Documentation | PredictLeads


object

Attributes of the CompanyLite object.


string

Company domain name.


string

nullable

Company name if available.


string

nullable

Company stock symbol (ticker) if available.

friendly_company_name


string

Company friendly name.

meta_title


string

Company website's meta title.

meta_description


string

Company website's meta title.

language


string

Company website's language.

location


string

Company location.

location_data


array

LocationData


object

The LocationData object.

city


string

nullable

state


string

nullable

zip_code


string

nullable

country


string

nullable

region


string

nullable

continent


string

nullable

fuzzy_match


boolean

nullable


object

Contains references to the Company-related objects listed in the included property.

parent_company

[optional]


object

Contains a reference to the Company-related CompanyLite object listed in the included property.

data


object

id


string

Format:

uuid

ID of the included CompanyLite object.

type


string

Constant:

"company"

Type of the included CompanyLite object.

redirects_to

[optional]


object

Contains a reference to the Company-related CompanyLite object listed in the included property.

data


object

id


string

Format:

uuid

ID of the included CompanyLite object.

type


string

Constant:

"company"

Type of the included CompanyLite object.

meta


object

Meta information about the redirect.

reason


string

nullable

One of the values:

"acquisition_merger", "locality", "rebranding"

Reason of the redirect.


array

Contains objects referenced in property relationships.


object

The CompanyLite object.

id


string

Format:

uuid

ID of the CompanyLite object.

type


string

Constant:

"company"

Type of the CompanyLite object.


object

Attributes of the CompanyLite object.


string

Company domain name.


string

nullable

Company name if available.


string

nullable

Company stock symbol (ticker) if available.

meta

[optional]


object

Meta information about CompaniesDataset object.


string

Represents schema version of objects.


string

Constant:

"active"

Represents record state of objects.

count

[optional]


integer

Example:

344

Total number of results.
NOTE: Only shown in API responses. For performance reasons it will be omitted from response if page request parameter is not provided.

CompaniesDataset object

{
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "title": "CompaniesDataset",
 "summary": "Information about companies.\n",
 "description": "Companies Dataset includes data such as Company Name, Meta Title, Meta Description,\nStructured Location Data, Ticker, Parent Company, Language and other basic company information.\n",
 "type": "object",
 "required": [
 "data",
 "included"
 ],
 "properties": {
 "data": {
 "type": "array",
 "items": {
 "title": "Company",
 "description": "The `Company` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes",
 "relationships"
 ],
 "properties": {
 "id": {
 "description": "ID of the `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `CompanyLite` object.",
 "const": "company"
 },
 "attributes": {
 "description": "Attributes of the `CompanyLite` object.",
 "type": "object",
 "required": [
 "domain",
 "company_name",
 "ticker",
 "friendly_company_name",
 "meta_title",
 "meta_description",
 "language",
 "location",
 "location_data"
 ],
 "properties": {
 "domain": {
 "description": "Company domain name.",
 "type": "string"
 },
 "company_name": {
 "description": "Company name if available.",
 "type": [
 "string",
 "null"
 ]
 },
 "ticker": {
 "description": "Company stock symbol (ticker) if available.",
 "type": [
 "string",
 "null"
 ]
 },
 "friendly_company_name": {
 "description": "Company friendly name.",
 "type": "string"
 },
 "meta_title": {
 "description": "Company website's meta title.",
 "type": "string"
 },
 "meta_description": {
 "description": "Company website's meta title.",
 "type": "string"
 },
 "language": {
 "description": "Company website's language.",
 "type": "string"
 },
 "location": {
 "description": "Company location.",
 "type": "string"
 },
 "location_data": {
 "type": "array",
 "items": {
 "title": "LocationData",
 "description": "The `LocationData` object.",
 "type": "object",
 "required": [
 "city",
 "state",
 "zip_code",
 "country",
 "region",
 "continent",
 "fuzzy_match"
 ],
 "properties": {
 "city": {
 "type": [
 "string",
 "null"
 ]
 },
 "state": {
 "type": [
 "string",
 "null"
 ]
 },
 "zip_code": {
 "type": [
 "string",
 "null"
 ]
 },
 "country": {
 "type": [
 "string",
 "null"
 ]
 },
 "region": {
 "type": [
 "string",
 "null"
 ]
 },
 "continent": {
 "type": [
 "string",
 "null"
 ]
 },
 "fuzzy_match": {
 "type": [
 "boolean",
 "null"
 ]
 }
 }
 }
 }
 }
 },
 "relationships": {
 "description": "Contains references to the `Company`-related objects listed in the `included` property.",
 "type": "object",
 "properties": {
 "parent_company": {
 "title": "CompanyToCompanyLiteRelationship",
 "description": "Contains a reference to the `Company`-related `CompanyLite` object listed in the `included` property.",
 "type": "object",
 "required": [
 "data"
 ],
 "properties": {
 "data": {
 "type": "object",
 "required": [
 "id",
 "type"
 ],
 "properties": {
 "id": {
 "description": "ID of the included `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the included `CompanyLite` object.",
 "const": "company"
 }
 }
 }
 }
 },
 "redirects_to": {
 "title": "CompanyToCompanyLiteRelationship",
 "description": "Contains a reference to the `Company`-related `CompanyLite` object listed in the `included` property.",
 "type": "object",
 "required": [
 "data",
 "meta"
 ],
 "properties": {
 "data": {
 "type": "object",
 "required": [
 "id",
 "type"
 ],
 "properties": {
 "id": {
 "description": "ID of the included `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the included `CompanyLite` object.",
 "const": "company"
 }
 }
 },
 "meta": {
 "description": "Meta information about the redirect.",
 "type": "object",
 "required": [
 "reason"
 ],
 "properties": {
 "reason": {
 "description": "Reason of the redirect.",
 "type": [
 "string",
 "null"
 ],
 "enum": [
 "acquisition_merger",
 "locality",
 "rebranding"
 ]
 }
 }
 }
 }
 }
 }
 }
 }
 }
 },
 "included": {
 "description": "Contains objects referenced in property `relationships`.",
 "type": "array",
 "items": {
 "title": "CompanyLite",
 "description": "The `CompanyLite` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes"
 ],
 "properties": {
 "id": {
 "description": "ID of the `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `CompanyLite` object.",
 "const": "company"
 },
 "attributes": {
 "description": "Attributes of the `CompanyLite` object.",
 "type": "object",
 "required": [
 "domain",
 "company_name",
 "ticker"
 ],
 "properties": {
 "domain": {
 "description": "Company domain name.",
 "type": "string"
 },
 "company_name": {
 "description": "Company name if available.",
 "type": [
 "string",
 "null"
 ]
 },
 "ticker": {
 "description": "Company stock symbol (ticker) if available.",
 "type": [
 "string",
 "null"
 ]
 }
 }
 }
 }
 }
 },
 "meta": {
 "description": "Meta information about `CompaniesDataset` object.\n",
 "type": "object",
 "required": [
 "schema_version",
 "record_state"
 ],
 "properties": {
 "schema_version": {
 "title": "Meta.SchemaVersion",
 "description": "Represents schema version of objects.\n",
 "type": "string"
 },
 "record_state": {
 "title": "Meta.RecordState",
 "description": "Represents record state of objects.\n",
 "type": "string",
 "const": "active"
 },
 "count": {
 "description": "Total number of results.\n \n**NOTE**: Only shown in API responses. For performance reasons it will be omitted from response\nif `page` request parameter is not provided.\n",
 "type": "integer",
 "example": 344
 }
 }
 }
 },
 "example": {
 "data": [
 {
 "id": "4d621799-d317-58ba-a967-d09e07a5391f",
 "type": "company",
 "attributes": {
 "domain": "hubspot.com",
 "company_name": "HubSpot, Inc.",
 "friendly_company_name": "HubSpot",
 "ticker": "NYSE:HUBS",
 "meta_title": "HubSpot | Software & Tools for your Business - Homepage",
 "meta_description": "HubSpot's CRM platform contains the marketing, sales, service, operations, and website-building software you need to grow your business.",
 "language": "en",
 "location": "Cambridge, Massachusetts, United States",
 "location_data": [
 {
 "city": "Cambridge",
 "state": "Massachusetts",
 "zip_code": null,
 "country": "United States",
 "region": null,
 "continent": null,
 "fuzzy_match": null
 }
 ]
 },
 "relationships": {}
 }
 ],
 "included": [],
 "meta": {
 "schema_version": "3.0",
 "record_state": "active"
 }
 }
}

1.2.3.
API Endpoints

Retrieve Company

1.3.
Job Openings Dataset

1.3.1.
Introduction

PredictLeads has historical jobs data since 2018 that includes over 190 million records, and is available for 1.6 million companies, which includes an average of 7 million active jobs at any given time.

Job Openings are sourced directly from company websites which includes their career subpages, and ATS integrations. All Jobs are categorized using industry-standard O*NET codes.

The Job Openings Dataset includes fields such as Job Opening Title, Job Opening URL, First Seen At, Last Seen At, Location, Category, Seniority, Description, Salary, Contract Type, O*NET Job Category Codes and other Job Opening information.

1.3.2.
Use cases

Sales Enablement platforms leverage Job Openings data to extend their lead search criteria.
Market Intelligence platforms use Job Openings data to track hiring trends.
Investment Companies keep track of headcount changes and leverage job descriptions to identify similar companies.

1.3.3.
Data Model

JobOpeningsDataset


object

data


array

JobOpening


object

The JobOpening object.

id


string

Format:

uuid

ID of the JobOpening object.

type


string

Constant:

"job_opening"

Type of the JobOpening object.


object

Attributes of the JobOpening object.

title


string

Job title.

description


string

nullable

JobOpening description.

url


string

Format:

uri

URL of the web page where the data was found.


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"

Date & time (ISO 8601) of when the JobOpening was first seen.


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"

Date & time (ISO 8601) of when the JobOpening was last seen.

last_processed_at


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"

Date & time (ISO 8601) of when the JobOpening was last sent to processing.

contract_types


array

Example:

[ "full time", "remote" ]

Zero or more types describing the JobOpening.

categories


array

Example:

[ "finance", "data_analysis" ]

Zero or more organizational categories of the JobOpening.

Items


string

One of the values:

"administration", "consulting", "data_analysis", "design", "directors", "education", "engineering", "finance", "healthcare_services", "human_resources", "information_technology", "internship", "legal", "management", "marketing", "military_and_protective_services", "operations", "purchasing", "product_management", "quality_assurance", "real_estate", "research", "sales", "software_development", "support", "manual_work", "food"

onet_data


object

Inferred O*NET data for this JobOpening. O*NET is a source and standardization of occupational information. More info on the O*NET data: onetonline.org.

code


string

nullable

Example:

"29-1021.00"

O*NET category code representing this JobOpening.

family


string

nullable

Example:

"Healthcare Practitioners and Technical"

O*NET family name matching the code for this JobOpening.

occupation_name


string

nullable

Example:

"Dentists, General"

O*NET occupation name matching the code for this JobOpening.

salary


string

nullable

Example:

"£40000 - £50000 GBP"

Raw salary string.

salary_data


object

Parsed raw salary data.

salary_low


number

nullable

Salary range lower bound. If salary is not a range both low and high values will be the same.

salary_high


number

nullable

Salary range upper bound.

salary_currency


string

nullable

Salary currency.

salary_low_usd


number

nullable

Salary range lower bound, converted to USD.

salary_high_usd


number

nullable

Salary range upper bound, converted to USD.

salary_time_unit


string

nullable

One of the values:

"hour", "day", "week", "month", "year", null

Salary time unit.

seniority


string

nullable

One of the values:

"owner", "founder", "c_level", "partner", "president", "vice_president", "head", "director", "manager", "non_manager"

Seniority inferred from the JobOpening title.

status


string

nullable

One of the values:

"closed", null

null or "closed" if keyword "job no longer available", "vacancy listing expired", "position filled", etc. is found on JobOpening site.

language


string

nullable

Language in which a JobOpening description is written.

location


string

nullable

Raw location string.

location_data


array

LocationData


object

The LocationData object.

city


string

nullable

state


string

nullable

zip_code


string

nullable

country


string

nullable

region


string

nullable

continent


string

nullable

fuzzy_match


boolean

nullable

tags


array

Includes keywords found under JobOpening description.


object

Contains references to the JobOpening-related objects listed in the included property.

company


object

Contains a reference to the JobOpening-related CompanyLite object listed in the included property.

data


object

id


string

Format:

uuid

ID of the included CompanyLite object.

type


string

Constant:

"company"

Type of the included CompanyLite object.


array

Contains objects referenced in property relationships.


object

The CompanyLite object.

id


string

Format:

uuid

ID of the CompanyLite object.

type


string

Constant:

"company"

Type of the CompanyLite object.


object

Attributes of the CompanyLite object.


string

Company domain name.


string

nullable

Company name if available.


string

nullable

Company stock symbol (ticker) if available.

meta

[optional]


object

Meta information about JobOpeningsDataset object.


string

Represents schema version of objects.

TechnologyDetectionsDataset


string

Constant:

"active"

Represents record state of objects.

count

[optional]


integer

Example:

344

Total number of results.
NOTE: Only shown in API responses. For performance reasons it will be omitted from response if page request parameter is not provided.

JobOpeningsDataset object

{
  "data": [
    {
      "id": "4d5ac23c-5824-427d-96c6-4e8d50a4241a",
      "type": "job_opening",
      "attributes": {
        "title": "AI Engineer",
        "description": "**AI Engineer**\n\n\n**$50K - $120K** /  0.10% - 0.50%  **Location** London, England, GB  **Job Type** Full-time  **Experience** Any (new grads ok)   Apply to Terra API and hundreds of other fast-growing YC startups with a single profile.    ****\n\nAPI for developers to connect to health data from wearables and…\n\n\n**About the role**\n\nWe work in super small teams, with extremely high velocity.\n\nWe are building multiple AI products, such as OdinAI, Graph API, and many more\n\nAs an AI engineer, you'll work in a small team, with maximum autonomy.\n\n* Be behind the curtain, creating, testing, and implementing AI models\n* Engage in data analysis, machine learning, and natural language processing.\n* Fine-tuning the AI's performance and many more\n\nPreferred background:\n\nBachelor's or Master's degree in STEM. Strong technical skills (e.g. familiarity with a programming language such as Python, JavaScript, or Ruby) Experience with growth marketing, product development, and user acquisition/retention\n\n\n**Must haves.**\n\n-Must have done this before, or be willing to learn fast.\n\n-Must be fast. We operate at 200mph, and so do you.\n\n-Must be relentless. We never stop, so you are even faster than us.\n\n-Must have customer driven. We think customers first and so should you.\n\n-Must be driven and go above and beyond.\n\n-Must be able to explain and communicate clearly.\n\n-Must be prepared to challenge us and disagree. We are thinking and acting as a team.\n\n-Must be able to work autonomously.\n\n-Must want to work hard.\n\n-Last but not least, you are genuinely a nice person.\n\n**Big plus** You are an athlete, or care about quantifying your data\n\n\n**About Terra API**\n\n**What we do**\n\nTerra is an API that makes it easy for apps to connect to wearables. Currently, apps and developers in the fitness, wellness, sleep, and other health spaces are using us. Terra was launched in early 2021, and since then we’ve been growing like crazy. But this is just the beginning.\n\n\n**The goal and vision**\n\nThink if Spotify and Netflix create music and movies based on your heart rate, and stress levels, in real time. We want to enable apps to achieve that reality, through our super easy to use API.\n\n\n**Funding**\n\nTo achieve our grand goal, we couldn’t have made it without the support from some incredible investors. We are lucky enough to be supported by , ,  and we were part of  batch.\n\n, and learn who we are \n\nLocation: London, United Kingdom",
        "url": "https://www.ycombinator.com/companies/terra-api/jobs/0f5CP0r-ai-engineer",
        "first_seen_at": "2025-01-23T20:12:48Z",
        "last_seen_at": "2025-01-25T20:12:07Z",
        "last_processed_at": "2025-01-25T20:25:23Z",
        "contract_types": [
          "full time"
        ],
        "categories": [
          "engineering"
        ],
        "onet_data": {
          "code": "15-1252.00",
          "family": "Computer and Mathematical",
          "occupation_name": "Software Developers"
        },
        "salary": "$50000 - $120000",
        "salary_data": {
          "salary_low": 50000.0,
          "salary_high": 120000.0,
          "salary_currency": "USD",
          "salary_low_usd": 50000.0,
          "salary_high_usd": 120000.0,
          "salary_time_unit": "year"
        },
        "seniority": "non_manager",
        "status": "closed",
        "language": "en",
        "location": "London, United Kingdom",
        "location_data": [
          {
            "city": "London",
            "state": null,
            "zip_code": null,
            "country": "United Kingdom",
            "region": null,
            "continent": null,
            "fuzzy_match": false
          }
        ],
        "tags": [
          "Growth",
          "Python",
          "Ruby",
          "JavaScript"
        ]
      },
      "relationships": {
        "company": {
          "data": {
            "id": "eb383981-96cf-5d24-8e09-15f71f35879e",
            "type": "company"
          }
        }
      }
    }
  ],
  "included": [
    {
      "id": "eb383981-96cf-5d24-8e09-15f71f35879e",
      "type": "company",
      "attributes": {
        "domain": "tryterra.co",
        "company_name": "Terra Enabling Developers, Ltd.",
        "ticker": null
      }
    }
  ],
  "meta": {
    "schema_version": "3.0",
    "record_state": "active"
  }
}

{
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "title": "JobOpeningsDataset",
 "summary": "Information about Job Openings sourced directly from company websites for highest accuracy and freshness.\n",
 "description": "PredictLeads has historical jobs data since 2018 that includes over 190 million records, and is available\nfor 1.6 million companies, which includes an average of 7 million active jobs at any given time.\n \nJob Openings are sourced directly from company websites which includes their career subpages, and ATS\nintegrations. All Jobs are categorized using industry-standard\n<a target=\"_blank\" rel=\"noopener\" href=\"https://www.onetonline.org/\">O\\*NET codes</a>.\n \nThe Job Openings Dataset includes fields such as Job Opening Title, Job Opening URL, First Seen At,\nLast Seen At, Location, Category, Seniority, Description, Salary, Contract Type, O\\*NET Job Category Codes\nand other Job Opening information.\n",
 "type": "object",
 "required": [
 "data",
 "included"
 ],
 "properties": {
 "data": {
 "type": "array",
 "items": {
 "title": "JobOpening",
 "description": "The `JobOpening` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes",
 "relationships"
 ],
 "properties": {
 "id": {
 "description": "ID of the `JobOpening` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `JobOpening` object.",
 "const": "job_opening"
 },
 "attributes": {
 "description": "Attributes of the `JobOpening` object.",
 "type": "object",
 "required": [
 "title",
 "description",
 "url",
 "first_seen_at",
 "last_seen_at",
 "last_processed_at",
 "contract_types",
 "categories",
 "onet_data",
 "salary",
 "salary_data",
 "seniority",
 "status",
 "language",
 "location",
 "location_data",
 "tags"
 ],
 "properties": {
 "title": {
 "description": "Job title.",
 "type": "string"
 },
 "description": {
 "description": "`JobOpening` description.",
 "type": [
 "string",
 "null"
 ]
 },
 "url": {
 "description": "URL of the web page where the data was found.",
 "type": "string",
 "format": "uri"
 },
 "first_seen_at": {
 "description": "Date & time (ISO 8601) of when the `JobOpening` was first seen.",
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "last_seen_at": {
 "description": "Date & time (ISO 8601) of when the `JobOpening` was last seen.",
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "last_processed_at": {
 "description": "Date & time (ISO 8601) of when the `JobOpening` was last sent to processing.",
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "contract_types": {
 "description": "Zero or more types describing the `JobOpening`.",
 "example": [
 "full time",
 "remote"
 ],
 "type": "array",
 "items": [
 {
 "type": "string"
 }
 ]
 },
 "categories": {
 "description": "Zero or more organizational categories of the `JobOpening`.",
 "example": [
 "finance",
 "data_analysis"
 ],
 "type": "array",
 "items": {
 "enum": [
 "administration",
 "consulting",
 "data_analysis",
 "design",
 "directors",
 "education",
 "engineering",
 "finance",
 "healthcare_services",
 "human_resources",
 "information_technology",
 "internship",
 "legal",
 "management",
 "marketing",
 "military_and_protective_services",
 "operations",
 "purchasing",
 "product_management",
 "quality_assurance",
 "real_estate",
 "research",
 "sales",
 "software_development",
 "support",
 "manual_work",
 "food"
 ]
 }
 },
 "onet_data": {
 "description": "Inferred O\\*NET data for this `JobOpening`. O\\*NET is a source and standardization of occupational information. More info on the O\\*NET data: onetonline.org.",
 "type": "object",
 "required": [
 "code",
 "family",
 "occupation_name"
 ],
 "properties": {
 "code": {
 "description": "O\\*NET category code representing this `JobOpening`.",
 "example": "29-1021.00",
 "type": [
 "string",
 "null"
 ]
 },
 "family": {
 "description": "O\\*NET family name matching the code for this `JobOpening`.",
 "example": "Healthcare Practitioners and Technical",
 "type": [
 "string",
 "null"
 ]
 },
 "occupation_name": {
 "description": "O\\*NET occupation name matching the code for this `JobOpening`.",
 "example": "Dentists, General",
 "type": [
 "string",
 "null"
 ]
 }
 }
 },
 "salary": {
 "description": "Raw salary string.",
 "example": "£40000 - £50000 GBP",
 "type": [
 "string",
 "null"
 ]
 },
 "salary_data": {
 "description": "Parsed raw salary data.",
 "type": "object",
 "required": [
 "salary_low",
 "salary_high",
 "salary_currency",
 "salary_low_usd",
 "salary_high_usd",
 "salary_time_unit"
 ],
 "properties": {
 "salary_low": {
 "description": "Salary range lower bound. If salary is not a range both low and high values will be the same.",
 "type": [
 "number",
 "null"
 ]
 },
 "salary_high": {
 "description": "Salary range upper bound.",
 "type": [
 "number",
 "null"
 ]
 },
 "salary_currency": {
 "description": "Salary currency.",
 "type": [
 "string",
 "null"
 ]
 },
 "salary_low_usd": {
 "description": "Salary range lower bound, converted to USD.",
 "type": [
 "number",
 "null"
 ]
 },
 "salary_high_usd": {
 "description": "Salary range upper bound, converted to USD.",
 "type": [
 "number",
 "null"
 ]
 },
 "salary_time_unit": {
 "description": "Salary time unit.",
 "enum": [
 "hour",
 "day",
 "week",
 "month",
 "year",
 null
 ]
 }
 }
 },
 "seniority": {
 "description": "Seniority inferred from the `JobOpening` title.",
 "type": [
 "string",
 "null"
 ],
 "enum": [
 "owner",
 "founder",
 "c_level",
 "partner",
 "president",
 "vice_president",
 "head",
 "director",
 "manager",
 "non_manager"
 ]
 },
 "status": {
 "description": "null or \"closed\" if keyword \"job no longer available\", \"vacancy listing expired\", \"position filled\", etc. is found on `JobOpening` site.",
 "enum": [
 "closed",
 null
 ]
 },
 "language": {
 "description": "Language in which a `JobOpening` description is written.",
 "type": [
 "string",
 "null"
 ]
 },
 "location": {
 "description": "Raw location string.",
 "type": [
 "string",
 "null"
 ]
 },
 "location_data": {
 "type": "array",
 "items": {
 "title": "LocationData",
 "description": "The `LocationData` object.",
 "type": "object",
 "required": [
 "city",
 "state",
 "zip_code",
 "country",
 "region",
 "continent",
 "fuzzy_match"
 ],
 "properties": {
 "city": {
 "type": [
 "string",
 "null"
 ]
 },
 "state": {
 "type": [
 "string",
 "null"
 ]
 },
 "zip_code": {
 "type": [
 "string",
 "null"
 ]
 },
 "country": {
 "type": [
 "string",
 "null"
 ]
 },
 "region": {
 "type": [
 "string",
 "null"
 ]
 },
 "continent": {
 "type": [
 "string",
 "null"
 ]
 },
 "fuzzy_match": {
 "type": [
 "boolean",
 "null"
 ]
 }
 }
 }
 },
 "tags": {
 "description": "Includes keywords found under `JobOpening` description.",
 "type": "array",
 "items": [
 {
 "type": "string"
 }
 ]
 }
 }
 },
 "relationships": {
 "description": "Contains references to the `JobOpening`-related objects listed in the `included` property.",
 "type": "object",
 "required": [
 "company"
 ],
 "properties": {
 "company": {
 "title": "JobOpeningToCompanyLiteRelationship",
 "description": "Contains a reference to the `JobOpening`-related `CompanyLite` object listed in the `included` property.",
 "type": "object",
 "required": [
 "data"
 ],
 "properties": {
 "data": {
 "type": "object",
 "required": [
 "id",
 "type"
 ],
 "properties": {
 "id": {
 "description": "ID of the included `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the included `CompanyLite` object.",
 "const": "company"
 }
 }
 }
 }
 }
 }
 }
 }
 }
 },
 "included": {
 "description": "Contains objects referenced in property `relationships`.",
 "type": "array",
 "items": {
 "title": "CompanyLite",
 "description": "The `CompanyLite` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes"
 ],
 "properties": {
 "id": {
 "description": "ID of the `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `CompanyLite` object.",
 "const": "company"
 },
 "attributes": {
 "description": "Attributes of the `CompanyLite` object.",
 "type": "object",
 "required": [
 "domain",
 "company_name",
 "ticker"
 ],
 "properties": {
 "domain": {
 "description": "Company domain name.",
 "type": "string"
 },
 "company_name": {
 "description": "Company name if available.",
 "type": [
 "string",
 "null"
 ]
 },
 "ticker": {
 "description": "Company stock symbol (ticker) if available.",
 "type": [
 "string",
 "null"
 ]
 }
 }
 }
 }
 }
 },
 "meta": {
 "description": "Meta information about `JobOpeningsDataset` object.\n",
 "type": "object",
 "required": [
 "schema_version",
 "record_state"
 ],
 "properties": {
 "schema_version": {
 "title": "Meta.SchemaVersion",
 "description": "Represents schema version of objects.\n",
 "type": "string"
 },
 "record_state": {
 "title": "Meta.RecordState",
 "description": "Represents record state of objects.\n",
 "type": "string",
 "const": "active"
 },
 "count": {
 "description": "Total number of results.\n \n**NOTE**: Only shown in API responses. For performance reasons it will be omitted from response\nif `page` request parameter is not provided.\n",
 "type": "integer",
 "example": 344
 }
 }
 }
 },
 "example": {
 "data": [
 {
 "id": "4d5ac23c-5824-427d-96c6-4e8d50a4241a",
 "type": "job_opening",
 "attributes": {
 "title": "AI Engineer",
 "description": "**AI Engineer**\n\n\n**$50K - $120K** / 0.10% - 0.50% **Location** London, England, GB **Job Type** Full-time **Experience** Any (new grads ok) Apply to Terra API and hundreds of other fast-growing YC startups with a single profile. ****\n\nAPI for developers to connect to health data from wearables and…\n\n\n**About the role**\n\nWe work in super small teams, with extremely high velocity.\n\nWe are building multiple AI products, such as OdinAI, Graph API, and many more\n\nAs an AI engineer, you'll work in a small team, with maximum autonomy.\n\n* Be behind the curtain, creating, testing, and implementing AI models\n* Engage in data analysis, machine learning, and natural language processing.\n* Fine-tuning the AI's performance and many more\n\nPreferred background:\n\nBachelor's or Master's degree in STEM. Strong technical skills (e.g. familiarity with a programming language such as Python, JavaScript, or Ruby) Experience with growth marketing, product development, and user acquisition/retention\n\n\n**Must haves.**\n\n-Must have done this before, or be willing to learn fast.\n\n-Must be fast. We operate at 200mph, and so do you.\n\n-Must be relentless. We never stop, so you are even faster than us.\n\n-Must have customer driven. We think customers first and so should you.\n\n-Must be driven and go above and beyond.\n\n-Must be able to explain and communicate clearly.\n\n-Must be prepared to challenge us and disagree. We are thinking and acting as a team.\n\n-Must be able to work autonomously.\n\n-Must want to work hard.\n\n-Last but not least, you are genuinely a nice person.\n\n**Big plus** You are an athlete, or care about quantifying your data\n\n\n**About Terra API**\n\n**What we do**\n\nTerra is an API that makes it easy for apps to connect to wearables. Currently, apps and developers in the fitness, wellness, sleep, and other health spaces are using us. Terra was launched in early 2021, and since then we’ve been growing like crazy. But this is just the beginning.\n\n\n**The goal and vision**\n\nThink if Spotify and Netflix create music and movies based on your heart rate, and stress levels, in real time. We want to enable apps to achieve that reality, through our super easy to use API.\n\n\n**Funding**\n\nTo achieve our grand goal, we couldn’t have made it without the support from some incredible investors. We are lucky enough to be supported by , , and we were part of batch.\n\n, and learn who we are \n\nLocation: London, United Kingdom",
 "url": "https://www.ycombinator.com/companies/terra-api/jobs/0f5CP0r-ai-engineer",
 "first_seen_at": "2025-01-23T20:12:48Z",
 "last_seen_at": "2025-01-25T20:12:07Z",
 "last_processed_at": "2025-01-25T20:25:23Z",
 "contract_types": [
 "full time"
 ],
 "categories": [
 "engineering"
 ],
 "onet_data": {
 "code": "15-1252.00",
 "family": "Computer and Mathematical",
 "occupation_name": "Software Developers"
 },
 "salary": "$50000 - $120000",
 "salary_data": {
 "salary_low": 50000.0,
 "salary_high": 120000.0,
 "salary_currency": "USD",
 "salary_low_usd": 50000.0,
 "salary_high_usd": 120000.0,
 "salary_time_unit": "year"
 },
 "seniority": "non_manager",
 "status": "closed",
 "language": "en",
 "location": "London, United Kingdom",
 "location_data": [
 {
 "city": "London",
 "state": null,
 "zip_code": null,
 "country": "United Kingdom",
 "region": null,
 "continent": null,
 "fuzzy_match": false
 }
 ],
 "tags": [
 "Growth",
 "Python",
 "Ruby",
 "JavaScript"
 ]
 },
 "relationships": {
 "company": {
 "data": {
 "id": "eb383981-96cf-5d24-8e09-15f71f35879e",
 "type": "company"
 }
 }
 }
 }
 ],
 "included": [
 {
 "id": "eb383981-96cf-5d24-8e09-15f71f35879e",
 "type": "company",
 "attributes": {
 "domain": "tryterra.co",
 "company_name": "Terra Enabling Developers, Ltd.",
 "ticker": null
 }
 }
 ],
 "meta": {
 "schema_version": "3.0",
 "record_state": "active"
 }
 }
}

1.3.4.
API Endpoints

1.4.
Technology Detections Dataset

1.4.1.
Introduction

The Technology Detections Dataset provides insights into the tech stack of a given company.

NOTE: If you're searching for general information about technologies please check the Technologies Dataset section.

Since 2018, PredictLeads has detected approximately 800 million technology adoptions for about 50 million companies.

The Technology Detection Dataset includes fields such as Technology Name, Technology ID, Ticker, First Seen At, Last Seen At, Seen on Subpages Count and other Technology Detection information.

1.4.2.
Use cases

Sales Enablement platforms leverage Technology Detections to identify a potential fit, to spot integration opportunities and to extend their lead search criteria.
Market Intelligence platforms use Technology Detections data to better understand technology adoption trends.
Investment Companies use Technology Detections to keep track of tech market shares and to spot which Technologies are getting adopted by e.g. Inc. 5000 companies.

1.4.3.
Data Model


object

data


array

TechnologyDetection


object

The TechnologyDetection object.

id


string

Format:

uuid

ID of the TechnologyDetection object.

type


string

Constant:

"technology_detection"

Type of the TechnologyDetection object.


object

Attributes of the TechnologyDetection object.


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"

Date & time (ISO 8601) of when the TechnologyDetection was first seen.


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"

Date & time (ISO 8601) of when the TechnologyDetection was last seen.

behind_firewall


boolean

score


number


object

Contains references to the TechnologyDetection-related objects listed in the included property.

company


object

Contains a reference to the TechnologyDetection-related CompanyLite object listed in the included property.

data


object

id


string

Format:

uuid

ID of the included CompanyLite object.

type


string

Constant:

"company"

Type of the included CompanyLite object.

seen_on_job_openings


object

Contains a reference to the TechnologyDetection-related JobOpeningLite objects listed in the included property.

data


array

Items


object

id


string

Format:

uuid

ID of the included JobOpeningLite object.

type


string

Constant:

"job_opening"

Type of the included JobOpeningLite object.

seen_on_subpages


object

Contains a reference to the TechnologyDetection-related DetectionOnSubpage objects listed in the included property.

data


array

Items


object

id


string

Format:

uuid

ID of the included DetectionOnSubpage object.

type


string

Constant:

"detection_on_subpage"

Type of the included DetectionOnSubpage object.

technology


object

Contains a reference to the TechnologyDetection-related TechnologyLite object listed in the included property.

data


object

id


string

Format:

uuid

ID of the included TechnologyLite object.

type


string

Constant:

"technology"

Type of the included TechnologyLite object.


array

Contains objects referenced in property relationships.

Items

One of

Discriminator property name:

"type"


object

The CompanyLite object.

id


string

Format:

uuid

ID of the CompanyLite object.

type


string

Constant:

"company"

Type of the CompanyLite object.


object

Attributes of the CompanyLite object.


string

Company domain name.


string

nullable

Company name if available.


string

nullable

Company stock symbol (ticker) if available.

TechnologyLite


object

The TechnologyLite object.

id


string

Format:

uuid

ID of the TechnologyLite object.

type


string

Constant:

"technology"

Type of the TechnologyLite object.


object

Attributes of the TechnologyLite object.

name


string

DetectionOnSubpage


object

The DetectionOnSubpage object.

id


string

Format:

uuid

ID of the DetectionOnSubpage object.

type


string

Constant:

"detection_on_subpage"

Type of the DetectionOnSubpage object.


object

Attributes of the DetectionOnSubpage object.


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"

subpage_url


string

Format:

uri

JobOpeningLite


object

The JobOpeningLite object.

id


string

Format:

uuid

ID of the JobOpeningLite object.

type


string

Constant:

"job_opening"

Type of the JobOpeningLite object.


object

Attributes of the JobOpeningLite object.


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"

Date & time (ISO 8601) of when the JobOpeningLite was first seen.


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"

Date & time (ISO 8601) of when the JobOpeningLite was last seen.

url


string

Format:

uri

URL of the web page where the data was found.

meta

[optional]


object

Meta information about TechnologyDetectionsDataset object.


string

Represents schema version of objects.


string

Constant:

"active"

Represents record state of objects.

count

[optional]


integer

Example:

344

Total number of results.
NOTE: Only shown in API responses. For performance reasons it will be omitted from response if page request parameter is not provided.

TechnologyDetectionsDataset object

{
  "data": [
    {
      "id": "344f5e7c-4dae-4814-8f45-ded70b2baa6a",
      "type": "technology_detection",
      "attributes": {
        "first_seen_at": "2022-12-08T10:40:41Z",
        "last_seen_at": "2025-01-11T15:37:18Z",
        "behind_firewall": false,
        "score": 1.0
      },
      "relationships": {
        "company": {
          "data": {
            "id": "9e0bf4ad-0792-58ba-94a0-cb12a5a853a2",
            "type": "company"
          }
        },
        "seen_on_job_openings": {
          "data": []
        },
        "seen_on_subpages": {
          "data": [
            {
              "id": "fc8ca4d4-2a57-4588-9dcd-84fe46ae2578",
              "type": "detection_on_subpage"
            },
            {
              "id": "786f683a-2bdd-484e-8313-3b4a7657818c",
              "type": "detection_on_subpage"
            },
            {
              "id": "03cc40c7-f835-4717-8977-c48f7de14412",
              "type": "detection_on_subpage"
            },
            {
              "id": "116a7c00-f62b-491d-aeca-2c827af8b0fc",
              "type": "detection_on_subpage"
            },
            {
              "id": "0554514a-e42d-4017-93d0-a131074e86ea",
              "type": "detection_on_subpage"
            },
            {
              "id": "a66a4e41-c3f2-4f0e-b4a1-7c48602ae223",
              "type": "detection_on_subpage"
            },
            {
              "id": "0635626f-de95-4c06-ae84-b96123929607",
              "type": "detection_on_subpage"
            },
            {
              "id": "eff83149-0a0b-41f2-b64d-e763e0b9169f",
              "type": "detection_on_subpage"
            },
            {
              "id": "653df380-c529-472b-b8e9-b6b7dd3c648e",
              "type": "detection_on_subpage"
            },
            {
              "id": "e91d0154-14d0-4a09-928f-2ab3bd69e9bf",
              "type": "detection_on_subpage"
            },
            {
              "id": "21ac8110-d928-454c-9c59-51640875ad89",
              "type": "detection_on_subpage"
            },
            {
              "id": "b3ee6546-219c-45f8-a314-a8a5aa7a6b80",
              "type": "detection_on_subpage"
            },
            {
              "id": "a8dca87f-c62b-456d-b2e9-317fc4a96705",
              "type": "detection_on_subpage"
            },
            {
              "id": "7a51bac1-50ed-415a-ae63-9303a9f45e89",
              "type": "detection_on_subpage"
            },
            {
              "id": "40fcea2d-77c9-44e2-812e-e8a0ddcfbfdc",
              "type": "detection_on_subpage"
            }
          ]
        },
        "technology": {
          "data": {
            "id": "aa139d7c-b2fd-5b76-8dac-97c9ba844c73",
            "type": "technology"
          }
        }
      }
    }
  ],
  "included": [
    {
      "id": "fc8ca4d4-2a57-4588-9dcd-84fe46ae2578",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2022-12-08T10:40:47Z",
        "last_seen_at": "2025-01-11T15:37:18Z",
        "subpage_url": "https://www.madkudu.com"
      }
    },
    {
      "id": "786f683a-2bdd-484e-8313-3b4a7657818c",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-11-26T14:12:22Z",
        "last_seen_at": "2024-12-27T14:15:38Z",
        "subpage_url": "https://www.madkudu.com/customers"
      }
    },
    {
      "id": "03cc40c7-f835-4717-8977-c48f7de14412",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-12-06T12:28:31Z",
        "last_seen_at": "2025-01-06T12:47:31Z",
        "subpage_url": "https://www.madkudu.com/customers/lucid"
      }
    },
    {
      "id": "116a7c00-f62b-491d-aeca-2c827af8b0fc",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-11-21T14:43:19Z",
        "last_seen_at": "2024-11-21T14:43:19Z",
        "subpage_url": "https://www.madkudu.com/sales-copilot"
      }
    },
    {
      "id": "0554514a-e42d-4017-93d0-a131074e86ea",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-11-21T14:43:33Z",
        "last_seen_at": "2024-11-21T14:43:33Z",
        "subpage_url": "https://www.madkudu.com/legal-center"
      }
    },
    {
      "id": "a66a4e41-c3f2-4f0e-b4a1-7c48602ae223",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-11-21T14:44:06Z",
        "last_seen_at": "2024-11-21T14:44:06Z",
        "subpage_url": "https://www.madkudu.com/privacy-center/privacy-notice-controller"
      }
    },
    {
      "id": "0635626f-de95-4c06-ae84-b96123929607",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-06-03T01:57:52Z",
        "last_seen_at": "2024-12-03T09:18:13Z",
        "subpage_url": "https://support.madkudu.com/hc/en-us"
      }
    },
    {
      "id": "eff83149-0a0b-41f2-b64d-e763e0b9169f",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-12-03T13:30:43Z",
        "last_seen_at": "2024-12-03T13:30:43Z",
        "subpage_url": "https://www.madkudu.com/contact-us"
      }
    },
    {
      "id": "653df380-c529-472b-b8e9-b6b7dd3c648e",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-12-28T04:30:07Z",
        "last_seen_at": "2024-12-28T04:30:07Z",
        "subpage_url": "https://www.madkudu.com/privacy-center/privacy"
      }
    },
    {
      "id": "e91d0154-14d0-4a09-928f-2ab3bd69e9bf",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-12-06T11:20:47Z",
        "last_seen_at": "2025-01-06T11:32:09Z",
        "subpage_url": "https://www.madkudu.com/customers/outsystems"
      }
    },
    {
      "id": "21ac8110-d928-454c-9c59-51640875ad89",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-12-07T13:01:15Z",
        "last_seen_at": "2025-01-07T13:03:02Z",
        "subpage_url": "https://www.madkudu.com/customers/invision"
      }
    },
    {
      "id": "b3ee6546-219c-45f8-a314-a8a5aa7a6b80",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-12-09T16:46:02Z",
        "last_seen_at": "2025-01-09T16:52:31Z",
        "subpage_url": "https://www.madkudu.com/integrations"
      }
    },
    {
      "id": "a8dca87f-c62b-456d-b2e9-317fc4a96705",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-12-09T16:51:36Z",
        "last_seen_at": "2025-01-09T16:56:51Z",
        "subpage_url": "https://www.madkudu.com/customers/marketmuse"
      }
    },
    {
      "id": "7a51bac1-50ed-415a-ae63-9303a9f45e89",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-12-11T13:13:33Z",
        "last_seen_at": "2025-01-11T13:19:08Z",
        "subpage_url": "https://www.madkudu.com/customers/algolia"
      }
    },
    {
      "id": "40fcea2d-77c9-44e2-812e-e8a0ddcfbfdc",
      "type": "detection_on_subpage",
      "attributes": {
        "first_seen_at": "2024-11-21T14:44:37Z",
        "last_seen_at": "2024-11-21T14:44:37Z",
        "subpage_url": "https://www.madkudu.com/privacy-center/cookie-notice"
      }
    },
    {
      "id": "aa139d7c-b2fd-5b76-8dac-97c9ba844c73",
      "type": "technology",
      "attributes": {
        "name": "Google Hosted Libraries"
      }
    },
    {
      "id": "9e0bf4ad-0792-58ba-94a0-cb12a5a853a2",
      "type": "company",
      "attributes": {
        "domain": "madkudu.com",
        "company_name": "MadKudu Inc.",
        "ticker": null
      }
    }
  ],
  "meta": {
    "schema_version": "3.0",
    "record_state": "active"
  }
}

{
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "title": "TechnologyDetectionsDataset",
 "summary": "Information about approximately 800 million detections of companies that use various technologies.\n",
 "description": "The Technology Detections Dataset provides insights into the tech stack of a given company.\n \n\n**NOTE**: If you're searching for general information about technologies please check the\n**<a href=\"https://docs.predictleads.com/v3/guide/technologies_dataset\">Technologies Dataset</a>**\nsection.\n \n\nSince 2018, PredictLeads has detected approximately 800 million technology adoptions for about\n50 million companies.\n \nThe Technology Detection Dataset includes fields such as Technology Name, Technology ID, Ticker,\nFirst Seen At, Last Seen At, Seen on Subpages Count and other Technology Detection information.\n",
 "type": "object",
 "required": [
 "data",
 "included"
 ],
 "properties": {
 "data": {
 "type": "array",
 "items": {
 "title": "TechnologyDetection",
 "description": "The `TechnologyDetection` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes",
 "relationships"
 ],
 "properties": {
 "id": {
 "description": "ID of the `TechnologyDetection` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `TechnologyDetection` object.",
 "const": "technology_detection"
 },
 "attributes": {
 "description": "Attributes of the `TechnologyDetection` object.",
 "type": "object",
 "required": [
 "first_seen_at",
 "last_seen_at",
 "behind_firewall",
 "score"
 ],
 "properties": {
 "first_seen_at": {
 "description": "Date & time (ISO 8601) of when the `TechnologyDetection` was first seen.",
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "last_seen_at": {
 "description": "Date & time (ISO 8601) of when the `TechnologyDetection` was last seen.",
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "behind_firewall": {
 "type": "boolean"
 },
 "score": {
 "type": "number"
 }
 }
 },
 "relationships": {
 "description": "Contains references to the `TechnologyDetection`-related objects listed in the `included` property.",
 "type": "object",
 "required": [
 "company",
 "seen_on_job_openings",
 "seen_on_subpages",
 "technology"
 ],
 "properties": {
 "company": {
 "title": "TechnologyDetectionToCompanyLiteRelationship",
 "description": "Contains a reference to the `TechnologyDetection`-related `CompanyLite` object listed in the `included` property.",
 "type": "object",
 "required": [
 "data"
 ],
 "properties": {
 "data": {
 "type": "object",
 "required": [
 "id",
 "type"
 ],
 "properties": {
 "id": {
 "description": "ID of the included `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the included `CompanyLite` object.",
 "const": "company"
 }
 }
 }
 }
 },
 "seen_on_job_openings": {
 "title": "TechnologyDetectionToJobOpeningLitesRelationship",
 "description": "Contains a reference to the `TechnologyDetection`-related `JobOpeningLite` objects listed in the `included` property.",
 "type": "object",
 "required": [
 "data"
 ],
 "properties": {
 "data": {
 "type": "array",
 "items": {
 "type": "object",
 "required": [
 "id",
 "type"
 ],
 "properties": {
 "id": {
 "description": "ID of the included `JobOpeningLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the included `JobOpeningLite` object.",
 "const": "job_opening"
 }
 }
 }
 }
 }
 },
 "seen_on_subpages": {
 "title": "TechnologyDetectionToDetectionOnSubpagesRelationship",
 "description": "Contains a reference to the `TechnologyDetection`-related `DetectionOnSubpage` objects listed in the `included` property.",
 "type": "object",
 "required": [
 "data"
 ],
 "properties": {
 "data": {
 "type": "array",
 "items": {
 "type": "object",
 "required": [
 "id",
 "type"
 ],
 "properties": {
 "id": {
 "description": "ID of the included `DetectionOnSubpage` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the included `DetectionOnSubpage` object.",
 "const": "detection_on_subpage"
 }
 }
 }
 }
 }
 },
 "technology": {
 "title": "TechnologyDetectionToTechnologyLiteRelationship",
 "description": "Contains a reference to the `TechnologyDetection`-related `TechnologyLite` object listed in the `included` property.",
 "type": "object",
 "required": [
 "data"
 ],
 "properties": {
 "data": {
 "type": "object",
 "required": [
 "id",
 "type"
 ],
 "properties": {
 "id": {
 "description": "ID of the included `TechnologyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the included `TechnologyLite` object.",
 "const": "technology"
 }
 }
 }
 }
 }
 }
 }
 }
 }
 },
 "included": {
 "description": "Contains objects referenced in property `relationships`.",
 "type": "array",
 "items": {
 "oneOf": [
 {
 "title": "CompanyLite",
 "description": "The `CompanyLite` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes"
 ],
 "properties": {
 "id": {
 "description": "ID of the `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `CompanyLite` object.",
 "const": "company"
 },
 "attributes": {
 "description": "Attributes of the `CompanyLite` object.",
 "type": "object",
 "required": [
 "domain",
 "company_name",
 "ticker"
 ],
 "properties": {
 "domain": {
 "description": "Company domain name.",
 "type": "string"
 },
 "company_name": {
 "description": "Company name if available.",
 "type": [
 "string",
 "null"
 ]
 },
 "ticker": {
 "description": "Company stock symbol (ticker) if available.",
 "type": [
 "string",
 "null"
 ]
 }
 }
 }
 }
 },
 {
 "title": "TechnologyLite",
 "description": "The `TechnologyLite` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes"
 ],
 "properties": {
 "id": {
 "description": "ID of the `TechnologyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `TechnologyLite` object.",
 "const": "technology"
 },
 "attributes": {
 "description": "Attributes of the `TechnologyLite` object.",
 "type": "object",
 "required": [
 "name"
 ],
 "properties": {
 "name": {
 "type": "string"
 }
 }
 }
 }
 },
 {
 "title": "DetectionOnSubpage",
 "description": "The `DetectionOnSubpage` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes"
 ],
 "properties": {
 "id": {
 "description": "ID of the `DetectionOnSubpage` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `DetectionOnSubpage` object.",
 "const": "detection_on_subpage"
 },
 "attributes": {
 "description": "Attributes of the `DetectionOnSubpage` object.",
 "type": "object",
 "required": [
 "first_seen_at",
 "last_seen_at",
 "subpage_url"
 ],
 "properties": {
 "first_seen_at": {
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "last_seen_at": {
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "subpage_url": {
 "type": "string",
 "format": "uri"
 }
 }
 }
 }
 },
 {
 "title": "JobOpeningLite",
 "description": "The `JobOpeningLite` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes"
 ],
 "properties": {
 "id": {
 "description": "ID of the `JobOpeningLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `JobOpeningLite` object.",
 "const": "job_opening"
 },
 "attributes": {
 "description": "Attributes of the `JobOpeningLite` object.",
 "type": "object",
 "required": [
 "first_seen_at",
 "last_seen_at",
 "url"
 ],
 "properties": {
 "first_seen_at": {
 "description": "Date & time (ISO 8601) of when the `JobOpeningLite` was first seen.",
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "last_seen_at": {
 "description": "Date & time (ISO 8601) of when the `JobOpeningLite` was last seen.",
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 },
 "url": {
 "description": "URL of the web page where the data was found.",
 "type": "string",
 "format": "uri"
 }
 }
 }
 }
 }
 ],
 "discriminator": {
 "propertyName": "type"
 }
 }
 },
 "meta": {
 "description": "Meta information about `TechnologyDetectionsDataset` object.\n",
 "type": "object",
 "required": [
 "schema_version",
 "record_state"
 ],
 "properties": {
 "schema_version": {
 "title": "Meta.SchemaVersion",
 "description": "Represents schema version of objects.\n",
 "type": "string"
 },
 "record_state": {
 "title": "Meta.RecordState",
 "description": "Represents record state of objects.\n",
 "type": "string",
 "const": "active"
 },
 "count": {
 "description": "Total number of results.\n \n**NOTE**: Only shown in API responses. For performance reasons it will be omitted from response\nif `page` request parameter is not provided.\n",
 "type": "integer",
 "example": 344
 }
 }
 }
 },
 "example": {
 "data": [
 {
 "id": "344f5e7c-4dae-4814-8f45-ded70b2baa6a",
 "type": "technology_detection",
 "attributes": {
 "first_seen_at": "2022-12-08T10:40:41Z",
 "last_seen_at": "2025-01-11T15:37:18Z",
 "behind_firewall": false,
 "score": 1.0
 },
 "relationships": {
 "company": {
 "data": {
 "id": "9e0bf4ad-0792-58ba-94a0-cb12a5a853a2",
 "type": "company"
 }
 },
 "seen_on_job_openings": {
 "data": []
 },
 "seen_on_subpages": {
 "data": [
 {
 "id": "fc8ca4d4-2a57-4588-9dcd-84fe46ae2578",
 "type": "detection_on_subpage"
 },
 {
 "id": "786f683a-2bdd-484e-8313-3b4a7657818c",
 "type": "detection_on_subpage"
 },
 {
 "id": "03cc40c7-f835-4717-8977-c48f7de14412",
 "type": "detection_on_subpage"
 },
 {
 "id": "116a7c00-f62b-491d-aeca-2c827af8b0fc",
 "type": "detection_on_subpage"
 },
 {
 "id": "0554514a-e42d-4017-93d0-a131074e86ea",
 "type": "detection_on_subpage"
 },
 {
 "id": "a66a4e41-c3f2-4f0e-b4a1-7c48602ae223",
 "type": "detection_on_subpage"
 },
 {
 "id": "0635626f-de95-4c06-ae84-b96123929607",
 "type": "detection_on_subpage"
 },
 {
 "id": "eff83149-0a0b-41f2-b64d-e763e0b9169f",
 "type": "detection_on_subpage"
 },
 {
 "id": "653df380-c529-472b-b8e9-b6b7dd3c648e",
 "type": "detection_on_subpage"
 },
 {
 "id": "e91d0154-14d0-4a09-928f-2ab3bd69e9bf",
 "type": "detection_on_subpage"
 },
 {
 "id": "21ac8110-d928-454c-9c59-51640875ad89",
 "type": "detection_on_subpage"
 },
 {
 "id": "b3ee6546-219c-45f8-a314-a8a5aa7a6b80",
 "type": "detection_on_subpage"
 },
 {
 "id": "a8dca87f-c62b-456d-b2e9-317fc4a96705",
 "type": "detection_on_subpage"
 },
 {
 "id": "7a51bac1-50ed-415a-ae63-9303a9f45e89",
 "type": "detection_on_subpage"
 },
 {
 "id": "40fcea2d-77c9-44e2-812e-e8a0ddcfbfdc",
 "type": "detection_on_subpage"
 }
 ]
 },
 "technology": {
 "data": {
 "id": "aa139d7c-b2fd-5b76-8dac-97c9ba844c73",
 "type": "technology"
 }
 }
 }
 }
 ],
 "included": [
 {
 "id": "fc8ca4d4-2a57-4588-9dcd-84fe46ae2578",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2022-12-08T10:40:47Z",
 "last_seen_at": "2025-01-11T15:37:18Z",
 "subpage_url": "https://www.madkudu.com"
 }
 },
 {
 "id": "786f683a-2bdd-484e-8313-3b4a7657818c",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-11-26T14:12:22Z",
 "last_seen_at": "2024-12-27T14:15:38Z",
 "subpage_url": "https://www.madkudu.com/customers"
 }
 },
 {
 "id": "03cc40c7-f835-4717-8977-c48f7de14412",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-12-06T12:28:31Z",
 "last_seen_at": "2025-01-06T12:47:31Z",
 "subpage_url": "https://www.madkudu.com/customers/lucid"
 }
 },
 {
 "id": "116a7c00-f62b-491d-aeca-2c827af8b0fc",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-11-21T14:43:19Z",
 "last_seen_at": "2024-11-21T14:43:19Z",
 "subpage_url": "https://www.madkudu.com/sales-copilot"
 }
 },
 {
 "id": "0554514a-e42d-4017-93d0-a131074e86ea",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-11-21T14:43:33Z",
 "last_seen_at": "2024-11-21T14:43:33Z",
 "subpage_url": "https://www.madkudu.com/legal-center"
 }
 },
 {
 "id": "a66a4e41-c3f2-4f0e-b4a1-7c48602ae223",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-11-21T14:44:06Z",
 "last_seen_at": "2024-11-21T14:44:06Z",
 "subpage_url": "https://www.madkudu.com/privacy-center/privacy-notice-controller"
 }
 },
 {
 "id": "0635626f-de95-4c06-ae84-b96123929607",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-06-03T01:57:52Z",
 "last_seen_at": "2024-12-03T09:18:13Z",
 "subpage_url": "https://support.madkudu.com/hc/en-us"
 }
 },
 {
 "id": "eff83149-0a0b-41f2-b64d-e763e0b9169f",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-12-03T13:30:43Z",
 "last_seen_at": "2024-12-03T13:30:43Z",
 "subpage_url": "https://www.madkudu.com/contact-us"
 }
 },
 {
 "id": "653df380-c529-472b-b8e9-b6b7dd3c648e",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-12-28T04:30:07Z",
 "last_seen_at": "2024-12-28T04:30:07Z",
 "subpage_url": "https://www.madkudu.com/privacy-center/privacy"
 }
 },
 {
 "id": "e91d0154-14d0-4a09-928f-2ab3bd69e9bf",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-12-06T11:20:47Z",
 "last_seen_at": "2025-01-06T11:32:09Z",
 "subpage_url": "https://www.madkudu.com/customers/outsystems"
 }
 },
 {
 "id": "21ac8110-d928-454c-9c59-51640875ad89",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-12-07T13:01:15Z",
 "last_seen_at": "2025-01-07T13:03:02Z",
 "subpage_url": "https://www.madkudu.com/customers/invision"
 }
 },
 {
 "id": "b3ee6546-219c-45f8-a314-a8a5aa7a6b80",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-12-09T16:46:02Z",
 "last_seen_at": "2025-01-09T16:52:31Z",
 "subpage_url": "https://www.madkudu.com/integrations"
 }
 },
 {
 "id": "a8dca87f-c62b-456d-b2e9-317fc4a96705",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-12-09T16:51:36Z",
 "last_seen_at": "2025-01-09T16:56:51Z",
 "subpage_url": "https://www.madkudu.com/customers/marketmuse"
 }
 },
 {
 "id": "7a51bac1-50ed-415a-ae63-9303a9f45e89",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-12-11T13:13:33Z",
 "last_seen_at": "2025-01-11T13:19:08Z",
 "subpage_url": "https://www.madkudu.com/customers/algolia"
 }
 },
 {
 "id": "40fcea2d-77c9-44e2-812e-e8a0ddcfbfdc",
 "type": "detection_on_subpage",
 "attributes": {
 "first_seen_at": "2024-11-21T14:44:37Z",
 "last_seen_at": "2024-11-21T14:44:37Z",
 "subpage_url": "https://www.madkudu.com/privacy-center/cookie-notice"
 }
 },
 {
 "id": "aa139d7c-b2fd-5b76-8dac-97c9ba844c73",
 "type": "technology",
 "attributes": {
 "name": "Google Hosted Libraries"
 }
 },
 {
 "id": "9e0bf4ad-0792-58ba-94a0-cb12a5a853a2",
 "type": "company",
 "attributes": {
 "domain": "madkudu.com",
 "company_name": "MadKudu Inc.",
 "ticker": null
 }
 }
 ],
 "meta": {
 "schema_version": "3.0",
 "record_state": "active"
 }
 }
}

1.4.4.
API Endpoints

1.5.
Technologies Dataset

1.5.1.
Introduction

Technologies dataset consists of some 30,000 technologies we track.

NOTE: If you're searching for technologies a given company is using please check the Technology Detections Dataset section.

Technologies are collected from script tags, IP ranges, cookies…, and also from job descriptions where companies mention them as required skill sets. Subpages checked for technology data are of the following categories: main, login, support, trust, retail, blog, news, press and news outlet.

The Technologies dataset includes fields such as Technology Name, Technology ID, Description, Category, Pricing Data and other Technology information.

1.5.2.
Data Model

TechnologiesDataset


object

data


array

Technology


object

The Technology object.

id


string

Format:

uuid

ID of the TechnologyLite object.

type


string

Constant:

"technology"

Type of the TechnologyLite object.


object

Attributes of the TechnologyLite object.

name


string

description


string

nullable

categories


array

Items


string

parent_categories


array

Items


string


string

nullable

url


string

nullable

Format:

uri

pricing_data


object

min_usd


number

nullable

max_usd


number

nullable

interval


string

nullable

tags


array

Items


string

created_at


string

Format:

date-time

Example:

"2024-09-25T16:09:53+00:00"


object

Contains references to the Technology-related objects listed in the included property.

company


object

Contains a reference to the Technology-related CompanyLite object listed in the included property.

data


object

id


string

Format:

uuid

ID of the included CompanyLite object.

type


string

Constant:

"company"

Type of the included CompanyLite object.


array

Contains objects referenced in property relationships.


object

The CompanyLite object.

id


string

Format:

uuid

ID of the CompanyLite object.

type


string

Constant:

"company"

Type of the CompanyLite object.


object

Attributes of the CompanyLite object.


string

Company domain name.


string

nullable

Company name if available.


string

nullable

Company stock symbol (ticker) if available.

meta

[optional]


object

Meta information about TechnologiesDataset object.


string

Represents schema version of objects.


string

Constant:

"active"

Represents record state of objects.

count

[optional]


integer

Example:

344

Total number of results.
NOTE: Only shown in API responses. For performance reasons it will be omitted from response if page request parameter is not provided.

TechnologiesDataset object

{
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "title": "TechnologiesDataset",
 "summary": "Information about approximately 30,000 technologies we track.\n",
 "description": "Technologies dataset consists of some 30,000 technologies we track.\n \n**NOTE**: If you're searching for technologies a given company is using please check the\n**<a href=\"https://docs.predictleads.com/v3/guide/technology_detections_dataset\">Technology Detections Dataset</a>**\nsection.\n \nTechnologies are collected from script tags, IP ranges, cookies…, and also from job descriptions where companies mention them as\nrequired skill sets. Subpages checked for technology data are of the following categories: main, login, support, trust, retail, blog, news, press and news outlet.\n \nThe Technologies dataset includes fields such as Technology Name, Technology ID, Description,\nCategory, Pricing Data and other Technology information.\n",
 "type": "object",
 "required": [
 "data",
 "included"
 ],
 "properties": {
 "data": {
 "type": "array",
 "items": {
 "title": "Technology",
 "description": "The `Technology` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes",
 "relationships"
 ],
 "properties": {
 "id": {
 "description": "ID of the `TechnologyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `TechnologyLite` object.",
 "const": "technology"
 },
 "attributes": {
 "description": "Attributes of the `TechnologyLite` object.",
 "type": "object",
 "required": [
 "name",
 "description",
 "categories",
 "parent_categories",
 "domain",
 "url",
 "pricing_data",
 "created_at"
 ],
 "properties": {
 "name": {
 "type": "string"
 },
 "description": {
 "type": [
 "null",
 "string"
 ]
 },
 "categories": {
 "type": "array",
 "items": {
 "type": "string"
 }
 },
 "parent_categories": {
 "type": "array",
 "items": {
 "type": "string"
 }
 },
 "domain": {
 "type": [
 "null",
 "string"
 ]
 },
 "url": {
 "type": [
 "null",
 "string"
 ],
 "format": "uri"
 },
 "pricing_data": {
 "type": "object",
 "required": [
 "interval",
 "max_usd",
 "min_usd",
 "tags"
 ],
 "properties": {
 "min_usd": {
 "type": [
 "null",
 "number"
 ]
 },
 "max_usd": {
 "type": [
 "null",
 "number"
 ]
 },
 "interval": {
 "type": [
 "null",
 "string"
 ]
 },
 "tags": {
 "type": "array",
 "items": {
 "type": "string"
 }
 }
 }
 },
 "created_at": {
 "type": "string",
 "format": "date-time",
 "example": "2024-09-25T16:09:53+00:00"
 }
 }
 },
 "relationships": {
 "description": "Contains references to the `Technology`-related objects listed in the `included` property.",
 "type": "object",
 "required": [
 "company"
 ],
 "properties": {
 "company": {
 "title": "TechnologyToCompanyLiteRelationship",
 "description": "Contains a reference to the `Technology`-related `CompanyLite` object listed in the `included` property.",
 "type": "object",
 "required": [
 "data"
 ],
 "properties": {
 "data": {
 "type": "object",
 "required": [
 "id",
 "type"
 ],
 "properties": {
 "id": {
 "description": "ID of the included `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the included `CompanyLite` object.",
 "const": "company"
 }
 }
 }
 }
 }
 }
 }
 }
 }
 },
 "included": {
 "description": "Contains objects referenced in property `relationships`.",
 "type": "array",
 "items": {
 "title": "CompanyLite",
 "description": "The `CompanyLite` object.",
 "type": "object",
 "required": [
 "id",
 "type",
 "attributes"
 ],
 "properties": {
 "id": {
 "description": "ID of the `CompanyLite` object.",
 "type": "string",
 "format": "uuid"
 },
 "type": {
 "description": "Type of the `CompanyLite` object.",
 "const": "company"
 },
 "attributes": {
 "description": "Attributes of the `CompanyLite` object.",
 "type": "object",
 "required": [
 "domain",
 "company_name",
 "ticker"
 ],
 "properties": {
 "domain": {
 "description": "Company domain name.",
 "type": "string"
 },
 "company_name": {
 "description": "Company name if available.",
 "type": [
 "string",
 "null"
 ]
 },
 "ticker": {
 "description": "Company stock symbol (ticker) if available.",
 "type": [
 "string",
 "null"
 ]
 }
 }
 }
 }
 }
 },
 "meta": {
 "description": "Meta information about `TechnologiesDataset` object.\n",
 "type": "object",
 "required": [
 "schema_version",
 "record_state"
 ],
 "properties": {
 "schema_version": {
 "title": "Meta.SchemaVersion",
 "description": "Represents schema version of objects.\n",
 "type": "string"
 },
 "record_state": {
 "title": "Meta.RecordState",
 "description": "Represents record state of objects.\n",
 "type": "string",
 "const": "active"
 },
 "count": {
 "description": "Total number of results.\n \n**NOTE**: Only shown in API responses. For performance reasons it will be omitted from response\nif `page` request parameter is not provided.\n",
 "type": "integer",
 "example": 344
 }
 }
 }
 },
 "example": {
 "data": [
 {
 "id": "70392f20-b531-53cc-afa6-26416c0d582d",
 "type": "technology",
 "attributes": {
 "name": "Salesforce",
 "description": "Salesforce is a cloud-based CRM platform that helps businesses manage customer interactions, sales, and marketing campaigns. It offers applications for sales, service, marketing, and analytics, enhancing operational efficiency and customer engagement. Known for its scalability, customization, and integration capabilities, Salesforce enables organizations to streamline processes and improve overall performance.",
 "categories": [
 "customer_relationship_management"
 ],
 "parent_categories": [
 "sales"
 ],
 "domain": "salesforce.com",
 "url": "https://www.salesforce.com",
 "pricing_data": {
 "min_usd": 300.0,
 "max_usd": 1000000.0,
 "interval": "yearly",
 "tags": [
 "low",
 "mid",
 "high",
 "enterprise",
 "b2b",
 "recurring",
 "saas"
 ]
 },
 "created_at": "2017-08-24T22:36:09Z"
 },
 "relationships": {
 "company": {
 "data": {
 "id": "9b638313-3fe3-5f5e-a19d-42e122cf06f9",
 "type": "company"
 }
 }
 }
 }
 ],
 "included": [
 {
 "id": "9b638313-3fe3-5f5e-a19d-42e122cf06f9",
 "type": "company",
 "attributes": {
 "domain": "salesforce.com",
 "company_name": "Salesforce, Inc.",
 "ticker": "NYSE:CRM"
 }
 }
 ],
 "meta": {
 "schema_version": "3.1",
 "record_state": "active"
 }
 }
}

1.5.3.
API Endpoints

1.6.
News Events Dataset

1.6.1.
Introduction

Since 2016, PredictLeads has detected over 7 million relevant news signals, which are available for 2 million companies globally.

The News Events are sourced from some 20 million blogs, news and PR sites and distilled into relevant categories by machine learning algorithms.

The News Events dataset includes fields such as Formatted Signal, Signal Category, Most Relevant Source URL, Article Sentence, Article Body, Article Author, Found At, Effective Date and other News Event information.

1.6.2.
Categories

Property in schema: category

Category	Description
`acquires`	Group name: acquisition Company acquired another company.
`merges_with`	Group name: acquisition Company merges with another company.
`sells_assets_to`	Group name: acquisition Company sells assets (like properties or warehouses) to other company.
`signs_new_client`	Group name: contract Company signs new client.
`files_suit_against`	Group name: corporate_challenges Company files suit against other company.
`has_issues_with`	Group name: corporate_challenges Company has vulnerability problems.
`closes_offices_in`	Group name: cost_cutting Company closes existing offices.
`decreases_headcount_by`	Group name: cost_cutting Company lays off employees.
`attends_event`	Group name: expansion Company attends an event.
`expands_facilities`	Group name: expansion Company opens new or expands existing facilities like warehouses, data centers, manufacturing plants etc.
`expands_offices_in`	Group name: expansion Company expands existing offices.
`expands_offices_to`	Group name: expansion Company opens new offices in another town, state, country or continent.
`increases_headcount_by`	Group name: expansion Company offers new job vacancies.
`opens_new_location`	Group name: expansion Company opens new service location like hotels, restaurants, bars, hospitals etc.
`goes_public`	Group name: investment Company issues shares to the public for the first time.
`invests_into`	Group name: investment Company invests into other company.
`invests_into_assets`	Group name: investment Company buys assets (like properties or warehouses) from other company.
`receives_financing`	Group name: investment Company receives financing like venture funding, loan, grant etc.
`hires`	Group name: leadership Company hired new executive or senior personnel.
`leaves`	Group name: leadership Executive or senior personnel left the company.
`promotes`	Group name: leadership Company promoted existing executive or senior personnel.
`retires_from`	Group name: leadership Executive or senior personnel retire from the company.
`integrates_with`	Group name: new_offering Company integrates with other company.
`is_developing`	Group name: new_offering Company is developing a new offering.
`launches`	Group name: new_offering Company launches new offering.
`partners_with`	Group name: partnership Company partners with other company.
`receives_award`	Group name: recognition Company or person at the company receives an award.
`recognized_as`	Group name: recognition Company or person at the company receives recognition.
`identified_as_competitor_of`	Group name: relational New or existing competitor was identified.

1.6.3.
Use cases

Sales Enablement platforms leverage News Events categories to identify relevant prospects and personalize their outreach.
Market Intelligence platforms use News Events data to score companies based on relevant news signals.
Investment Companies keep track of company activity and score potential investment opportunities.

1.6.4.
Data Model

NewsEventsDataset


object

data


array

NewsEvent


object

The NewsEvent object.

id


string

Format:

uuid

ID of the NewsEvent object.

type


string

Constant:

"news_event"

Type of the NewsEvent object.