Schema library b2b-intel

Return a company profile from a public page.

Pass this JSON Schema and a public source URL to/extract/json. Return a consistent company record for enrichment, research preparation, or an internal data product.

Use this schema The JSON file

tabstack.ai/pricing

TEXT

MARKDOWN

LINKS

extract.tsTypeScript

const res = await client.extract.json({
  url: 'https://example.com/pricing',
  json_schema: {
    type: 'object',
    properties: {
      plan: { type: 'string' },
      price: { type: 'number' },
    },
  },
})

res = client.extract.json(
    url='https://example.com/pricing',
    json_schema={
        'type': 'object',
        'properties': {
            'plan': {'type': 'string'},
            'price': {'type': 'number'},
        },
    },
)

tabstack extract json https://example.com/pricing \
  --schema '{"type":"object","properties":{"plan":{"type":"string"},"price":{"type":"number"}}}'

What it captures

Fields in this company profile.

Schema for B2B company profile data including firmographics, funding, and contact info.

Field	Type	What it holds
`name`	string, required	Legal or commonly-used company name.
`domain`	string, required	Primary website domain of the company.
`description`	string	Short description or tagline of the company.
`founded_year`	number	Year the company was founded.
`headquarters_city`	string	City of the company's headquarters.
`headquarters_country`	string	Country of the company's headquarters.
`employee_count`	number	Approximate number of employees.
`employee_range`	string	Employee count range band.
`industry`	string	Primary industry of the company.
`categories`	array	List of category or vertical tags for the company.
`funding_stage`	string	Latest funding stage of the company.
`total_funding_usd`	number	Total funding raised in USD.
`last_funding_date`	string	Date of the most recent funding round.
`investors`	array	List of known investors.
`revenue_range`	string	Estimated annual revenue range.
`is_public`	boolean	Whether the company is publicly traded.
`stock_ticker`	string	Stock ticker symbol if publicly traded.
`stock_exchange`	string	Stock exchange where the company is listed.
`linkedin_url`	string	LinkedIn company page URL.
`twitter_handle`	string	Twitter/X handle of the company.
`github_org`	string	GitHub organization name.
`phone`	string	Company main phone number.
`email`	string	Company main contact email.
`technologies`	array	Technologies detected in use by the company.
`products`	array	Names of products or services offered.
`competitors`	array	List of known or identified competitors.
`page_title`	string	Title of the source page. Tabstack auto-fills this from page metadata when left empty.
`favicon`	string	Favicon URL of the source page. Tabstack auto-fills this from page metadata when left empty.

Example

Inspect and validate the response shape.

The example below is generated from the schema to demonstrate its structure. Edit the object or paste a real response to validate it in your browser.

What it checks

Pass or fail, and the first reason why.

Whether the text parses as JSON, whether the top level is an object, and whether each field the schema requires is present at the declared type. A null is allowed anywhere. Every key you ask for is present. A field the page does not state can come back null, empty, a placeholder number, or a guessed value. Validate values, not just keys.

Example data, not a live response.

Usage

Send the schema with your source URL.

The schema travels with the request rather than living on your account, so the same call can send a trimmed version for one page and the full one for another. Every key you ask for is present. A field the page does not state can come back null, empty, a placeholder number, or a guessed value. Validate values, not just keys.

company.tsTypeScript

import schema from './company-profile.json'

const res = await client.extract.json({
  url: 'https://example.com/pricing',
  json_schema: schema,
})

tabstack extract json 'https://example.com/pricing' \
  --schema @./company-profile.json

Adaptation

Make the schema match your application.

The schema is a starting point, not a guarantee that every source page contains every field. Three things are worth doing before you write one into your system, and the schema-authoring guide covers the rest.

Remove what you do not need

A shorter schema is a smaller response and fewer fields to handle.

Describe the ambiguous ones

A description tells Extract what to look for when a label could mean two things.

Validate before you store

Check the returned object against the schema rather than trusting it.

Related schemas

Other schemas in this category.

Same category: api documentation endpoint.
Same category: competitor profile.
Same category: funding round.
The job rather than the object: the Extract API.