Company API

Finding detailed information on public companies is straightforward. Finding the same information for private companies is much more difficult.

We have mined government filings to identify over 28 million public and private companies, their subsidiaries, their officers and employees, their intellectual and physical property and even government connections. These details are often the sort that are not openly published on corporate websites.

We are now making these details available for use in other applications or data research projects through an easy-to-use Company API.

  1. Overview
  2. Request
  3. Response
  4. Examples
  5. Datasources
  6. Obtaining a Key


Let’s say you wanted to find out more about Google. Specifically you want to find related companies (e.g. “YouTube”), areas of expertise (e.g., “Search”), related people (e.g. “Sergey Brin”) and publications (e.g. “System and Methods for Automatically Creating Lists”).

Using the Company API you can submit a name and get in return a list of companies, expertise, people and publications associated with the company.


All of the Data APIs are RESTful and return JSON.


Each Data API uses our company domain and a dedicated “api” subdomain:


Our Data APIs will roll out gradually and the semantics are likely to change as we add features and increase the datatypes we support. For this reason all current requests should use the “v1″ prefix:


The Company API uses a single action called “companies”. This will return aliases, related companies, skills, people, brands and publications for a single company.


name Required This is the full name of the company you are looking for. Try to identify the exact legal name that is likely to appear on official documents (including the correct suffix?). The Company API will return related names to help you find the exact one (or more) you are looking for.
key Required Each application requires a key. Check here for details on getting a key.

Note: parameters must be URL encoded, including replacing blank spaces with %20.

See the Examples sections for variations.


The Company API returns up to seven types of data related to the company name submitted. A typical response looks like:

  "aliases": [
    "Google Inc",
  "companies": [
    "YouTube Inc",
    "Google Payments"],
  "people": [
    "Larry Page",
    "Sergey Brin"],
  "specialties": [
    "electric digital data processing",
    "information retrieval",
    "user interface"],
  "brands": [
  "locations": [
    "1600 Amphitheatre Pky, Mountain View, CA",
    "Palo Alto, CA"],
  "publications": [
    "Retaining wall masonry block",
    "System and method for reorganizing data storage in accordance with usage frequency",
    "Methods and apparatus for serving relevant advertisements"]


Aliases includes various other names that may be alternatives to the company name given. For instance, “Google Inc” returns “Google” and “Google Incorporated”. These variations all appear in public documents and may include misspellings, different suffixes and different word orders.

Each alias may be called separately to return related entities and publications associated with that name. In subsequent versions we will add the ability to include/exclude any of these aliases.


Companies includes companies or institutions such as subsidiaries with which this person has been affiliated. For instance, “Google ” returns “YouTube” and “Google Payments”.

Companies are not always explicitly identified as being a company. We look at entity type, role on the filing and inclusion of certain keywords in the name to determine if it is a company. These are not always correct.

Company affiliations are sometimes disclosed explicitly, such as in the Appendix 21 of a Form 10K. More often they are discovered by finding similar names, addresses and matching employees. Company affiliations include but are not limited to:

Each company may then be looked up using the Company API.


People includes people with whom this company has been affiliated. For instance, “Google Inc” returns “Simon Tong” and “Mark Pearson”. These people have appeared on public documents alongside the company.

Person affiliations include but are not limited to:

  • - inventors on a patent
  • - administrator on a filing
  • - lawyer advising on a filing
  • - disclosed relationship as manager, director or shareholder
  • - disclosed employer on campaign contributions


Specialties include the most common technologies which with this company is affiliated. For instance, “Google Inc” returns “search”, “machine learning”, etc.

We identify and score unique skills by mining millions of publications and factoring in word frequency, patent classifications, inventors and other signals. This is a non-trivial problem and requires a large number of frequent but not useful terms to be filtered out.


Brands include the most common phrases which with this company is affiliated. For instance, “Google Inc” returns “YouTube” and “”Blogger”.

We identify and score unique brands by mining millions of trademarks and product filings. Each brand can be further examined using the Brand API.


Locations includes address with which this company has been affiliated. For instance, “Google Inc” returns “1600 Amphitheatre Pky, Mountain View, CA” and “Palo Alto, CA”.

These addresses have appeared on public documents as either the company’s explicit address or the primary address on the filing. This means that it only includes addresses that are one degree separated from the company. It does not include second-degree relationships such as addresses affiliated with one or more of the affiliated persons.

Most addresses have been normalized and deduplicated using longitude and latitude. In many instances the address will not include details down to the street level. In these cases it will only include city and country.


Publications are all those documents on which the person appears. The full list of document types appears here.




In the first version this information comes from across all record types.

Obtaining a Key

If you are interested in advance access, please contact us at [email protected].


We investigate and acquire datasets from around the world using automated data retrieval and "deep web" crawling methods.


Our analysts use our existing library of proprietary ETL tools to return clean and structured data in any format your business requires.


Raw data is rarely good enough by itself. We use advanced natural language and machine learning methods to extract entities, from people to addresses, so you can find information, not just data.


At over 200 million records, 1 billion entities and relationships and 88 countries, our existing dataset of companies, people, intellectual property, legal and financial filings make for powerful supplements to your existing data.


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