Company Data

Fixpoint pre-extracts structured data about companies, giving you a comprehensive starting point for the company data you need for your applications, data workflows, or AI agents. If you want, you can further enrich this data via web scraping, or use the pre-extracted company data.

Here's a list of the data points available for a company:

company founder info: who they are, their past experiences
company description
business model and product descriptions
competitors
company stats: employee counts, HQ location, founding year
fundraising data: amount raised, investors, valuation
recent news
and more!

Using the API

HTTP API: GET /v1/companies/{company_id}
Python SDK: FixpointClient.companies.get(company_id) (support coming soon)
API spec (opens in a new tab)
API response schema: CompanyData (see schemas at bottom of API spec (opens in a new tab))

The company ID can be either a company name or a company domain. For example, either "Anthropic" or "anthropic.com".

# Python support coming soon

Enriching with more company datapoints

The company data API endpoint gives you a lot of comprehensive data, and we're always expanding it. But maybe there is extra data you want to mix in to a company data profile for your data pipelines. A couple ideas:

Look at all the news articles, filter them down to ones that list new customers, and extract the "customers" of a company
Inspect the company website and determine if they are vertical SaaS and, if so, what vertical they serve.

You can use Fixpoint's extraction API to do this. Here's a quick implementation of enriching the news data:

import os
 
from fixpoint.client import FixpointClient
from fixpoint.client.types import CreateRecordExtractionRequest, WebpageSource
 
client = FixpointClient(api_key=os.environ["FIXPOINT_API_KEY"])
 
company_data = client.companies.get("anthropic")
 
questions = [
    "Is this article about a new customer of Anthropic?",
    "If so, who is the new customer?"
]
news_scrapes = []
for news_item in company_data.news:
    scrape = client.extractions.record.create(
        CreateRecordExtractionRequest(
            source=WebpageSource(url=news_item.url),
            questions=questions,
        )
    )
    news_scrapes.append(scrape)

Soon, you will be able to save your data lookups and enrichments in a custom dataset. This way, each time you look up a particular company, Fixpoint will use cached data for stable datapoints (such as the founding team), and refresh data that changes frequently, such as news articles.

This saves you time (latency) and money, and prevents a lot of headaches around ETL workflows and transforming data into your required format.

Parsing Extraction (Single Site)