Northdata Company Scraper

Northdata Scraper

From SilentFlow. Creators of Facebook Search Scraper and Pinterest Scraper, with 600,000+ combined lifetime runs.

Every European company, structured: name, registry, officers, address, financials, events, industry. Search by name or feed direct profile URLs. Pay per result, proxies included. In seconds, not hours.

How it works

✨ Why teams choose this over other Northdata scrapers

Tired of paying for thin Northdata search lists with 6 fields per row? Still copy-pasting registry numbers and director names from Northdata one company at a time? Running into actors that crash on French SIREN, Belgian VAT, or UK Companies House formats?

• 💰 Pay per result, not per minute. No compute costs, proxies included. You pay for rows delivered, period.
• 🏢 Full profile, not just the search list. Other Northdata scrapers stop at the result list (name, city, registry number). This one opens each company and pulls 25+ fields including directors, founding date, corporate purpose, industry classification, and full address.
• 📈 Revenue, earnings and headcount on the row. The latest published figures sit next to the company name, with the year-by-year history (each value tagged with its source publication) and the balance sheet lines underneath. Screen targets by size without opening a single page.
• 🪪 LEI and every national identifier. LEI code, Siren and Siret, Companies House number, trade register entry and stock tickers, ready for entity matching and sanctions screening.
• 🕸️ Related companies. Acquisitions, mergers, break-ups, control agreements and shareholdings, each with its date, to map a holding structure from one profile.
• 👥 Real director and officer data, and people search. Names, roles, appointment dates and Northdata person URLs on every company. Switch the result type to People to list directors by name with every company they are tied to.
• 🌍 Country filter. Keep only the companies registered in one country, so a common name stops returning homonyms from the rest of Europe.
• 🌍 Works across the EU. UK Companies House, French SIREN, German Handelsregister, Belgian KBO, Dutch KvK, Italian REA, Spanish Mercantil, Nordic and Baltic registries. Single output schema.
• 🎯 Smart routing on exact matches. When your query matches a single company by name, the scraper jumps straight to its profile and returns the full record. No empty list to sift through.
• 🔗 Industry breadcrumbs included. Every record carries its NACE-style industry classification path, so you can segment leads by sector without a separate lookup.
• 🛡 High reliability. Profiles served by Northdata sometimes shift between languages and locales. Output is normalised regardless of source language.
• 📦 Stable output schema. Same JSON keys for every country and every registry type. Drop it into your warehouse without country-specific transforms.

🎯 What you can do with Northdata data

Team	What they build
Sales	Enrich a list of 5,000 EU companies with director names, registry IDs, and founding dates before outreach
Compliance and KYC	Verify counterparty registry numbers and screen named directors against sanctions and PEP lists
M&A and corporate development	Map ownership, find sister companies, check the corporate purpose of acquisition targets
Investigative journalism	Trace company histories, name changes, and address moves through historical events
Credit and risk	Flag liquidation status, watch for sudden registered office changes, monitor recent capital events
Recruitment	Identify Director and Managing Director names at target firms across France, Germany, the UK
Procurement and supplier intel	Vet European suppliers by legal form, industry code, and operating status
Research and policy	Pull thousands of registered businesses by industry and country for market sizing

📥 Input parameters

Field	Type	Default	Notes
searchQueries	array of strings	[]	Company names, director names, keywords or register numbers. Each query reads up to 45 matches, the most Northdata lists for one search. Unique-name queries open the company directly.
startUrls	array of URLs	[]	Northdata company or person profile URLs (e.g. https://www.northdata.com/Rolls-Royce%20plc,%20London/Companies%20House%2001003142) or search result URLs. Profile URLs are delivered as given; search URLs are read page after page.
country	string	any	Keep only companies and people registered in one country. Pick it, or type a code (de, deu) or an English name (Germany).
resultType	string	companies	companies, people (directors and officers, with the companies they are tied to) or both.
maxItems	integer	100	Hard cap on total rows returned across all queries and URLs.
maxResultsPerQuery	integer	empty	Cap each query on its own (1 to 45), so every name in a list gets its share of rows.
includeOfficers	boolean	true	Opens each result's profile for officers, revenue, earnings, employees, financial history, balance sheet, LEI, identifiers, publications and related companies. Set to false for a fast listing-only mode.
debugMode	boolean	false	Verbose logs for debugging.

You need at least one of searchQueries or startUrls.

📊 Output data

Each item is one European company, or one person when the result type includes people. Output is the same shape whether the source was a search query or a direct URL.

Example A: listed company with its financials

{
  "recordType": "company",
  "northdataUrl": "https://www.northdata.com/VOLKSWAGEN%20AG,%20Wolfsburg/Amtsgericht%20Braunschweig%20HRB%20100484",
  "northdataId": "4562491040071680",
  "name": "VOLKSWAGEN AG",
  "foundingDate": "1961-04-27",
  "status": "active",
  "leiCode": "529900NNUPAGGOMPXZ31",
  "address": { "country": "DE", "street": "Berliner Ring 2", "postalCode": "38440", "locality": "Wolfsburg" },
  "register": { "court": "Amtsgericht Braunschweig HRB", "number": "100484", "uniqueKey": "DE_100484" },
  "nationalIds": [
    { "value": "District Court of Braunschweig HRB 100484", "source": "German Trade Register Company Profile" },
    { "value": "Siren 853801629", "source": "Sirene database of enterprises and their establishments (legal entities)" }
  ],
  "industry": [{ "name": "Manufacture of motor vehicles" }],
  "revenue": 321913000000,
  "earnings": 7323000000,
  "totalAssets": 665791000000,
  "equity": 188779000000,
  "currency": "EUR",
  "financialYear": 2025,
  "financials": [
    { "metric": "Revenue", "year": 2025, "value": 321913000000, "formattedValue": "€321.9B", "currency": "EUR", "publicationTitle": "Stock exchange listed companies - Financial Data", "publicationDate": "2025-12-31" },
    { "metric": "Earnings", "year": 2025, "value": 7323000000, "formattedValue": "€7.32B", "currency": "EUR", "publicationTitle": "Stock exchange listed companies - Financial Data", "publicationDate": "2025-12-31" }
  ],
  "balanceSheets": [
    {
      "section": "Assets",
      "date": "2025-12-31",
      "currency": "EUR",
      "lines": [
        { "name": "Total Assets", "value": 665791000000, "formattedValue": "€665.8B", "level": 0 },
        { "name": "Total Current Assets", "value": 253776000000, "formattedValue": "€253.8B", "level": 1 },
        { "name": "Cash and Cash Equivalents", "value": 38801000000, "formattedValue": "€38.8B", "level": 2 }
      ]
    }
  ],
  "officers": [
    { "name": "Blume, Oliver Ingo", "givenName": "Oliver Ingo", "familyName": "Blume", "role": "CEO", "dateAppointed": "2018-04-23", "url": "https://www.northdata.com/Blume,%20Oliver%20Ingo,%20K%C3%B6nigslutter/qme" }
  ],
  "relatedCompanies": [
    { "name": "AUDI AG", "relationship": "Acquisition", "date": "2024-06-04" },
    { "name": "Volkswagen Financial Services Europe AG", "relationship": "Acquisition", "date": "2023-08-30" }
  ],
  "publications": [
    { "date": "2026-11-04", "title": "85 trademark filings (28 wordmarks, 12 figurative marks, 2 word figurative marks, 7 other marks): AIRS, ALLVIA, AMEO …", "source": "German Patent and Trademark Office (Trademark Records)", "url": "https://www.northdata.com/?id=5859327126274048" }
  ],
  "events": [
    { "date": "1961-04-27", "type": "Registration", "category": "History", "description": "Registration" }
  ],
  "scrapedAt": "2026-11-08T13:34:30Z"
}

Example B: a person found by a People search

{
  "recordType": "person",
  "northdataUrl": "https://www.northdata.com/Blume,%20Oliver%20Ingo,%20K%C3%B6nigslutter/qme",
  "name": "Oliver Ingo Blume",
  "givenName": "Oliver Ingo",
  "familyName": "Blume",
  "address": { "country": "DE", "locality": "Königslutter" },
  "companies": [
    { "name": "Bentley Motors Ltd.", "url": "https://www.northdata.com/Bentley%20Motors%20Ltd%C2%B7,%20Crewe/Companies%20House%2000992897" },
    { "name": "Dr. Ing. h.c. F. Porsche AG", "url": "https://www.northdata.com/Dr%C2%B7%20Ing%C2%B7%20h%C2%B7c%C2%B7%20F%C2%B7%20Porsche%20AG,%20Stuttgart/HRB%20730623" },
    { "name": "VOLKSWAGEN AG", "url": "https://www.northdata.com/VOLKSWAGEN%20AG,%20Wolfsburg/Amtsgericht%20Braunschweig%20HRB%20100484" },
    { "name": "Verband der Automobilindustrie (VDA)" }
  ],
  "searchQuery": "Oliver Blume",
  "scrapedAt": "2026-11-08T13:33:54Z"
}

Example C: UK public company with directors

{
  "northdataUrl": "https://www.northdata.com/Rolls-Royce%20plc,%20London/Companies%20House%2001003142",
  "name": "Rolls-Royce plc",
  "foundingDate": "1971-02-23",
  "address": {
    "country": "GB",
    "street": "90 York Way",
    "postalCode": "N1 9FX",
    "locality": "London"
  },
  "register": {
    "court": "Companies House",
    "number": "01003142",
    "uniqueKey": "GB_01003142"
  },
  "industry": [
    { "name": "Repair and maintenance of civilian air and spacecraft" }
  ],
  "officers": [
    {
      "name": "Varsellona, Maria Rosaria",
      "givenName": "Maria Rosaria",
      "familyName": "Varsellona",
      "role": "Director",
      "url": "https://www.northdata.com/Varsellona,%20Maria%20Rosaria,%20London/cwc",
      "address": { "country": "GB", "locality": "London" }
    }
  ],
  "breadcrumbs": ["Companies", "Repair and maintenance of civilian air and spacecraft", "Rolls-Royce plc"],
  "scrapedAt": "2026-05-15T17:40:21Z"
}

🗂️ Data fields

Every company carries these fields. Empty fields are omitted from the JSON.

Identity

Field	Type	Notes
name	string	Legal name as listed on Northdata, includes legal form suffix
alternateName	string	Former or trading name when Northdata exposes it
foundingDate	string	ISO date of incorporation
status	string	active, liquidation, terminated, insolvency
northdataUrl	string	Canonical Northdata profile URL
northdataId	string	Internal Northdata ID

Address

Field	Type	Notes
address.country	string	Country code or country name
address.street	string	Registered street
address.postalCode	string	Postal code
address.locality	string	City
address.lat	number	Geocoded latitude when available
address.lng	number	Geocoded longitude when available

Registry

Field	Type	Notes
register.court	string	Companies House, Amtsgericht, Siren, KBO, KvK, REA, etc.
register.number	string	Registration number as stored at the registry
register.uniqueKey	string	Country-prefixed deduplication key

People

Field	Type	Notes
officers[].name	string	Full name
officers[].givenName	string	First name
officers[].familyName	string	Family name
officers[].role	string	Director, Managing Director, Liquidator, etc.
officers[].url	string	Northdata person profile URL
officers[].address	object	Country and locality when published

Industry and purpose

Field	Type	Notes
industry[].name	string	Human-readable industry classification
corporatePurpose	string	Text of the registered corporate purpose
breadcrumbs	array	Northdata hierarchy path

Identifiers

Field	Type	Notes
leiCode	string	Legal Entity Identifier, when the company has one
nationalIds[].value	string	Every identifier on the profile: trade register entry, Siren, Siret, Companies House number, stock tickers, LEI
nationalIds[].source	string	The register or database it comes from

Financials

Figures appear where Northdata publishes them for free, most often for listed companies and German, Austrian, Belgian and Nordic filings. A figure Northdata keeps for its premium plan is left out, never guessed.

Field	Type	Notes
revenue	number	Latest published revenue
earnings	number	Latest published earnings (profit or loss)
employees	number	Latest published headcount
totalAssets	number	Latest balance sheet total
equity	number	Latest equity
currency	string	ISO currency of the figures (EUR, GBP, NOK...)
financialYear	number	Year of the latest figures
financials[]	array	Year-by-year history, one entry per metric and year: metric (Revenue, Earnings, Employees, Total assets, Public funding, Patents...), year, value, formattedValue, currency, consolidated, estimate, publicationTitle, publicationDate
balanceSheets[]	array	Latest balance sheet, one entry per side (Assets, Liabilities and equity) with its date, currency, source and lines (name, value, formattedValue, level in the tree)

Network, publications and history

Field	Type	Notes
relatedCompanies[]	array	Companies linked by an acquisition, merger, break-up, control agreement or shareholding: name, relationship, date, url when Northdata links it
publications[]	array	The 20 latest register filings, annual reports, patents and announcements: date, title, source, url
mentions[]	array	The 20 latest filings of other companies that name this one
events[].date	string	ISO date
events[].type	string	Registration, Capital change, Name or legal form change, Address change, Management change, Merger, acquisition or control, Trademark, Funding, Liquidation...
events[].category	string	The Northdata timeline it belongs to: History, Persons, Merger & Acquisition & Control, Marketing & Tech
events[].description	string	Human-readable description of the event

People rows

When resultType is people or both, a person is one row with recordType set to person.

Field	Type	Notes
recordType	string	company or person
name, givenName, familyName	string	The person's names
address.locality, address.country	string	Where Northdata places the person
companies[]	array	Companies the person is tied to: name, and url when the profile is read

Metadata

Field	Type	Notes
searchQuery	string	The query that produced this row, when relevant
scrapedAt	string	ISO 8601 timestamp at extraction

🚀 Examples

Look up one company by name

{
  "searchQueries": ["Siemens Energy"],
  "maxItems": 5
}

Build a 200-row enrichment of UK aerospace players

{
  "searchQueries": ["aerospace"],
  "maxItems": 200,
  "includeOfficers": true
}

Pull a single profile by direct URL

{
  "startUrls": [
    { "url": "https://www.northdata.com/Rolls-Royce%20plc,%20London/Companies%20House%2001003142" }
  ]
}

Get the list of directors for ten target companies

{
  "startUrls": [
    { "url": "https://www.northdata.com/Rolls-Royce%20plc,%20London/Companies%20House%2001003142" },
    { "url": "https://www.northdata.com/Jaguar%20Land%20Rover%20Ltd%C2%B7,%20Coventry/Companies%20House%2001672070" },
    { "url": "https://www.northdata.com/Imperial%20Tobacco%20Ltd%C2%B7,%20Bristol/Companies%20House%2001860181" }
  ],
  "includeOfficers": true,
  "maxItems": 10
}

German companies only, five best matches per name

{
  "searchQueries": ["Robert Bosch", "Siemens", "Continental"],
  "country": "DE",
  "maxResultsPerQuery": 5,
  "maxItems": 15
}

Map a director's mandates

{
  "searchQueries": ["Oliver Blume"],
  "resultType": "people",
  "maxItems": 10
}

Listing-only mode for a fast first pass

{
  "searchQueries": ["software", "fintech", "logistics"],
  "maxItems": 90,
  "includeOfficers": false
}

🤖 Copy to your AI assistant

Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor.

silentflow/northdata-scraper on Apify. Call: ApifyClient("TOKEN").actor("silentflow/northdata-scraper").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items for results. Key inputs: searchQueries (array of strings, company names, director names, keywords or register numbers, up to 45 matches each, unique names redirect to a single profile), startUrls (array of URL objects, Northdata company, person or search URLs), country (ISO-2 code or English name, keeps only rows registered there), resultType (companies, people or both, default companies), maxItems (integer, default 100, max 10000), maxResultsPerQuery (integer 1-45, optional per-query cap), includeOfficers (boolean, default true, opens each result's profile for officers, financials, identifiers, publications, related companies). At least one of searchQueries or startUrls required. Output per result: recordType (company/person), name, givenName, familyName, alternateName, foundingDate (ISO), status (active/liquidation/terminated/insolvency), leiCode, northdataUrl, northdataId, address (country ISO-2, street, postalCode, locality, lat, lng), register (court, number, uniqueKey), nationalIds (value, source), industry, segmentCodes (isic/nace/naics/uksic/wz2025), corporatePurpose, revenue, earnings, employees, totalAssets, equity, currency, financialYear, financials (metric, year, value, currency, consolidated, estimate, publicationTitle, publicationDate), balanceSheets (section, date, currency, lines: name, value, level), officers (name, role, dateAppointed, dateEnded, url), companies (for people: name, url), relatedCompanies (name, relationship, date, url), publications and mentions (date, title, source, url), events (date, type, category, description), breadcrumbs, searchQuery, scrapedAt. Full actor spec (input schema with all params/enums/defaults, output dataset fields, README): GET https://api.apify.com/v2/acts/silentflow~northdata-scraper/builds/default (Bearer TOKEN) → inputSchema, actorDefinition.storages.dataset, readme. Get token: https://console.apify.com/account/integrations

💻 Integrations

Enrich a list of leads in Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

leads = ["Siemens Energy", "Rolls-Royce plc", "Volkswagen AG"]

run = client.actor("silentflow/northdata-scraper").call(run_input={
    "searchQueries": leads,
    "includeOfficers": True,
    "maxItems": 200,
})

for company in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(company["name"], company["register"]["uniqueKey"],
          [o["name"] for o in company.get("officers", [])])

Build a director map of UK aerospace in Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const { defaultDatasetId } = await client
  .actor('silentflow/northdata-scraper')
  .call({
    searchQueries: ['aerospace London', 'aerospace Bristol'],
    includeOfficers: true,
    maxItems: 100,
  });

const { items } = await client.dataset(defaultDatasetId).listItems();

const directors = items.flatMap(c =>
  (c.officers || []).map(o => ({ company: c.name, name: o.name, role: o.role }))
);

console.table(directors);

Export the dataset to CSV for your sales team

curl "https://api.apify.com/v2/datasets/DATASET_ID/items?format=csv&token=YOUR_APIFY_TOKEN" \
  > northdata_leads.csv

📈 Performance

Workload	Run time	Items
Single search query, 5 companies, officers enabled	~1s	5
Three search queries, 30 companies, officers enabled	~6s	30
100 direct profile URLs with officers	~25s	100
1,000 profile URLs in listing mode	~3m	1,000

Times are indicative and vary with Northdata response time and proxy availability.

💾 Data export

The dataset is downloadable from the Apify console in JSON, CSV, Excel, RSS, HTML, and XML.

For programmatic exports, use the dataset API:

https://api.apify.com/v2/datasets/DATASET_ID/items?format=csv&token=YOUR_APIFY_TOKEN
https://api.apify.com/v2/datasets/DATASET_ID/items?format=json&clean=true&token=YOUR_APIFY_TOKEN

You can also pipe results live into BigQuery, S3, or your own webhook by configuring an Apify integration on the actor.

💡 Tips for best results

1. For B2B prospecting, run searches by industry keyword + city (e.g. "fintech Berlin", "logistics Rotterdam"). Unique company names redirect to a single profile and use one credit instead of fifteen.
2. To dedupe across multiple queries, key on register.uniqueKey. Two queries that surface the same company will share that key.
3. Turn off includeOfficers for first-pass exploration when you only need names and registry numbers. Turn it back on for shortlisted leads.
4. For compliance use cases, always store the raw northdataUrl and scrapedAt alongside the record. That gives you an auditable pointer back to the source.
5. When Northdata exposes geo coordinates (address.lat, address.lng), feed them straight into your CRM or map tool to cluster leads by region.

❓ FAQ

What countries does this cover? All countries Northdata indexes, including the UK, France, Germany, Belgium, Netherlands, Italy, Spain, Austria, Switzerland, Nordic countries, and Eastern Europe. Output schema is identical across countries.

What is the difference between this and the older Northdata search scraper on Apify? The older actor only returns the search list with a handful of fields. This one opens every matched company's profile and pulls 25+ fields including directors, address, registry court, founding date, industry, corporate purpose, and event history.

Do I need a Northdata account? No. The scraper extracts publicly available data. No login, no API key, nothing to set up.

How fresh is the data? The scraper pulls live from northdata.com at request time. Northdata refreshes its data continuously from official registries, often within days of publication.

How does pagination work? Each search returns up to fifteen results per page and Northdata lists at most 45 matches for one search. The scraper reads every page automatically until maxItems or maxResultsPerQuery is reached or the results run out. To build a longer list, run several narrower queries (a keyword plus a city, or several company names) in one go.

Can I search for people instead of companies? Yes. Set resultType to people and search a name such as Oliver Blume. Each person comes back as one row with the companies they are tied to and, with full profiles on, the link to each of those companies. both keeps companies and people in the same dataset, each row marked by recordType.

How do I keep only German (or French, or UK) companies? Set country. Rows registered elsewhere are left out before any profile is read, so a common name like BMW no longer brings back homonyms from other countries.

What if my query matches one company exactly? Northdata redirects to that company's profile. The scraper detects this and returns the full profile as a single result, not a list.

Can I run multiple queries in one run? Yes. Pass any number of strings in searchQueries. Results across queries are merged and deduped on register.uniqueKey.

Do you return financial figures like revenue? Yes, wherever Northdata shows them on the public profile: the latest revenue, earnings, employees, total assets and equity on the row itself, the year-by-year history with the publication each figure comes from, and the balance sheet lines. Northdata keeps some figures for its premium plan, most often for UK and French companies; those stay empty rather than guessed. In a test run on Robert Bosch GmbH, 4 of the first 15 matches came back with their revenue.

Are the directors verified? Names come directly from Northdata's profile, which sources from public registries (Companies House, Handelsregister, etc.). For regulated use cases, verify against the source registry.

Why is my country sometimes a name (France) and sometimes a code (GB)? Northdata mixes locale formats by source registry. We pass through what is exposed publicly. Both forms are unambiguous and country names are written in English.

Can I get historical events older than what is shown? Northdata stores events going back to the original registration. The scraper returns every event Northdata exposes for that company.

What happens if a profile URL changes? Northdata occasionally renames profile URLs when a company changes name or city. If a saved URL stops working, search the new name and use the fresh URL going forward.

⚖️ Legal

This Actor extracts publicly available data from northdata.com. It does not bypass any login, paywall, or CAPTCHA. Northdata aggregates information from official public registries. Users are responsible for complying with northdata.com terms of service and applicable laws in their jurisdiction, including GDPR rules around the use of personal data such as director names. The data returned is informational; verify accuracy against the source registry for regulated or contractual use cases.

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• eBay Listings - eBay Listings Scraper
• Europages Deep Dive Extractor - Europages Deep Dive Extractor | VAT, Decision Makers, ISO Certs
• Europages - Europages Scraper | Suppliers and B2B Companies
• GasBuddy - GasBuddy Scraper | Gas Prices by Station
• Goofish - Goofish Detail Scraper | Listings, Prices and Sellers
• Vinted - Vinted Scraper
• Walmart - Walmart Scraper | Prices, Reviews, Sellers, Availability
• Walmart - Walmart Product Scraper

💼 Jobs

• ZipRecruiter - ZipRecruiter Jobs Scraper | Salary, Company & Location Filters
• Indeed - Indeed Company Reviews Scraper
• Multi Board - Multi Board Job Scraper
• Jobright - Jobright Scraper | Jobs, Salaries and H1B Sponsors
• Jora - Jora Jobs Scraper
• LinkedIn Job Search - LinkedIn Job Search Scraper | Salaries & Seniority
• Malt - Malt Scraper | Freelance Profiles
• Glassdoor Job Listings - Glassdoor Job Listings Scraper
• 🔥 Glassdoor - 🔥 Glassdoor Scraper
• Malt Freelancer - Malt Freelancer Scraper
• ATS - ATS Jobs Scraper | Greenhouse, Lever and Ashby
• Glassdoor - Glassdoor Jobs Scraper
• Arbeitsagentur - Arbeitsagentur Jobs Scraper
• Cutshort - Cutshort Jobs Scraper | Salaries, Skills and Companies
• Dice - Dice Jobs Scraper | US Tech Jobs, Salaries, Skills
• Dice Tech - Dice Tech Jobs Scraper
• iimjobs - iimjobs Jobs Scraper | MBA, Finance and Hirist Tech Jobs
• Indeed - Indeed Jobs Scraper | Job Listings in 73 Countries
• Instahyre - Instahyre Jobs Scraper | Companies, Recruiters and Ratings
• Jora - Jora Scraper | Jobs in Australia, New Zealand, Singapore
• StepStone - StepStone Scraper
• Welcome to the Jungle - Welcome to the Jungle Job Scraper
• YCombinator - YCombinator Jobs Scraper | Startup Jobs, Salaries and Founders
• All - All Jobs Scraper
• Arbeitsagentur - Arbeitsagentur Scraper | German and Austrian Job Board
• iimjobs - iimjobs Scraper | Jobs, Companies and Recruiters
• Indeed - Indeed Companies Scraper | Reviews, Salaries, Interviews
• Indeed - Indeed Jobs Scraper | NLP Skills
• LinkedIn - LinkedIn Jobs Scraper
• Naukri & NaukriGulf - Naukri & NaukriGulf Jobs Scraper
• Seek - Seek Job Scraper
• Welcome to the Jungle - Welcome to the Jungle Scraper | Jobs and Company Data
• Ziprecruiter - Ziprecruiter Scraper

🏠 Real estate

• SeLoger - SeLoger Scraper | Real Estate Listings
• Realtor Rental Listings - Realtor Rental Listings Scraper
• Airbnb Professional Host - Airbnb Professional Host Scraper | Emails, Phones, SIRET
• Airbnb Pro Host Contact & - Airbnb Pro Host Contact & Email Scraper
• Trulia Rental Listings - Trulia Rental Listings Scraper
• Bien'ici - Bien'ici Scraper | Property Listings
• Rightmove - Rightmove Scraper
• SeLoger - SeLoger Scraper | French Property Listings and Agencies
• Airbnb Search - Airbnb Search Scraper
• Bienici - Bienici Scraper
• Idealista - Idealista Scraper
• Realestate.com.au - Realestate.com.au Scraper
• Airbnb Search - Airbnb Search Scraper | Prices, Fees, Amenities, Hosts
• Anjuke - Anjuke Scraper | Rental Listings, Prices and Agents
• Idealista - Idealista Scraper
• Realtor Rental - Realtor Rental Scraper
• Trulia Rental - Trulia Rental Scraper | US Rentals, Prices, Pet Policy
• Zillow - Zillow Scraper

📣 Social media

• LinkedIn Post Search - LinkedIn Post Search Scraper | Keywords, Hashtags & Profiles
• Facebook Search - Facebook Search Scraper
• Instagram - Instagram Story Scraper | Stories & Highlights
• LinkedIn Leads - LinkedIn Leads Scraper | Sales Navigator Export
• Facebook Search - Facebook Search Profiles Scraper | People by Name or Keyword
• YouTube - YouTube Channel Scraper | Videos, Shorts and Views
• TikTok - TikTok Scraper
• Instagram Engagement - Instagram Engagement Scraper
• TikTok Trend - TikTok Trend Scraper | Trending Hashtags and Videos
• Discord - Discord Scraper | Servers, Member Counts and Invites
• Douyin - Douyin Comments Scraper | Comments, Likes and IP Regions
• Likee - Likee Scraper | Videos, Hashtags and Creators
• Meta Ad Library - Meta Ad Library Scraper
• OnlyFans - OnlyFans Creator Scraper
• OnlyFans - OnlyFans Profile Scraper
• Reddit - Reddit Scraper | Posts, Comments and Subreddits
• Skool Community - Skool Community Scraper
• Bandsintown - Bandsintown Scraper | Concerts and Tour Dates
• Discord - Discord Profiles Scraper | Users, Badges and Server Tags
• Facebook Thread - Facebook Thread Profiles Scraper | Followers, Bios & Engagement
• Kuaishou - Kuaishou Scraper | Videos, Comments and Creator Stats
• LinkedIn Ads Library - No Cookies - LinkedIn Ads Library Scraper - No Cookies
• LinkedIn Event - LinkedIn Event Scraper
• LinkedIn Hashtag & - LinkedIn Hashtag & Post Scraper | No Cookies
• Pinterest - Pinterest Ads Scraper | Ad Library, Reach & Targeting
• Pinterest - Pinterest Profiles Scraper | Followers, Emails and Bios
• Pinterest - Pinterest Videos Scraper | Video Downloader, MP4 Links, Stats
• Reddit - Reddit Comments Scraper | Search, Threads and Replies
• Reddit - Reddit Profiles Scraper | User Karma, Activity and Communities
• Reddit - Reddit Scraper | Comments, Posts and Users
• RedNote - RedNote Videos Scraper | Downloader, Transcripts and Stats
• Snapchat - Snapchat Contacts Scraper | Phones, Emails and Websites
• Snapchat - Snapchat Videos Scraper | Spotlight Videos, MP4 and Stats
• TikTok Creative - TikTok Creative Ads Scraper | Top Ads, Landing Pages & Metrics
• TikTok Lookalike - TikTok Lookalike Scraper | Influencers, Emails and Engagement
• Xigua - Xigua Scraper | Videos, Creators and Downloads
• YouTube Autocomplete - YouTube Autocomplete Scraper | Keyword Suggestions
• Facebook - Facebook Company Scraper | Emails, Phones, Ratings
• Facebook Business Page - Facebook Business Page Scraper
• Kwai - Kwai Scraper | Videos, Creators and Hashtags
• RedNote - RedNote Detail Scraper | Xiaohongshu Details, Images, Videos
• Skool Group - Skool Group Scraper
• Snapchat - Snapchat Ads Scraper | Ad Library, Impressions & Targeting
• TwitchTracker - TwitchTracker Scraper | Twitch Streamer Stats and Rankings
• Weibo - Weibo Scraper | Posts, Profiles and Engagement
• YouTube - YouTube Transcript Scraper

🏢 Business data

• Tencent - Tencent Scraper | Maps Places, Phones and Ratings
• LinkedIn Company Search - LinkedIn Company Search Scraper | Profiles & Firmographics
• LinkedIn People Search - LinkedIn People Search Scraper | Profiles & Companies
• LinkedIn Sales Navigator - LinkedIn Sales Navigator Scraper
• Bilibili - Bilibili Scraper | Videos, Profiles, Comments, Danmaku
• Ctrip - Ctrip Scraper | Attractions, Tickets and Reviews
• SoftwareAdvice - SoftwareAdvice Scraper | Reviews, Ratings and Pros & Cons
• Teachable Course - Teachable Course Scraper
• Website Tech Stack - Website Tech Stack Scraper
• Zomato - Zomato Reviews Scraper | Restaurant Ratings and Replies
• 2GIS - 2GIS Reviews Scraper | Ratings, Photos and Owner Replies
• Teachable - Courses, Prices & Instructors - Teachable Scraper - Courses, Prices & Instructors
• Trustpilot - Trustpilot Scraper | Reviews, Ratings and Company Contacts

✈️ Travel

• Google Maps - Google Maps Scraper
• Flight Price - Flight Price Scraper
• Booking.com Hotel - Booking.com Hotel Scraper
• Kakao - Kakao Scraper | Map Places, Reviews and Phones
• OpenTable - OpenTable Reviews Scraper | Restaurant Reviews and Ratings
• TheFork - TheFork Scraper | Restaurants, Menus and Ratings
• Trip - Trip Reviews Scraper | Hotel Reviews and Ratings
• Booking - Booking Scraper | Hotel Prices, Photos, Availability

🎯 Lead generation

• Dealroom - Dealroom Scraper | Companies and Investors
• ZocDoc - ZocDoc Scraper | Doctors, Reviews and Availability
• UK Companies House - UK Companies House Enricher
• CNPJ Brazilian - CNPJ Brazilian Company Enricher
• Google Ads Transparency - Google Ads Transparency Scraper
• PagesJaunes - PagesJaunes Scraper | French Business Emails and SIRET
• BuiltWith - BuiltWith Scraper | Tech Stacks and Top Sites
• Company Data - Company Data Scraper | Emails, Phones and Tech Stack
• Dealroom Startup Data - Dealroom Startup Data Scraper
• Domain - Domain Enricher
• French Company Prospector - French Company Prospector
• G2 - G2 Reviews Scraper
• Justdial - Justdial Companies Scraper | Business Leads, Phones and Emails
• KVK - KVK Scraper | Dutch Companies and SBI Codes
• PagesJaunes - PagesJaunes Business Scraper
• SEC - SEC Scraper | EDGAR Filings and Company Data
• SIRET - SIRET Company Enricher
• SpyFu - SpyFu Scraper | SEO, PPC and Competitor Data
• Sunbiz - Sunbiz Companies Scraper | New Florida Business Leads
• Sunbiz - Sunbiz Scraper | Florida Companies and Officers
• USPTO - USPTO Scraper | Trademark Search and Status
• Clutch - Clutch Scraper | Agencies, Reviews, Ratings, Services
• Clutch Agency - Clutch Agency Scraper
• SIRET French - SIRET French Company Enricher
• ThomasNet Suppliers - ThomasNet Suppliers Scraper
• ZocDoc - ZocDoc Scraper

🔎 SEO

• Similarweb - Similarweb Scraper | Website Traffic, Rankings and Competitors
• Apple - Apple Reviews Scraper | App Store Reviews and Ratings
• Apple - Apple Scraper | App Store Apps, Ratings and Charts
• Bing - Bing Enricher Scraper | Mobile Friendly Test and Indexing
• Google News - Google News Scraper
• Scribd - Scribd Scraper | Documents, Authors and Views

📈 Marketing

• Douyin - Douyin Transcript Scraper | Subtitles and Speech to Text

🎬 Video

• Pexels - Pexels Scraper | Photos, Videos and Download Stats

📰 News

• ForexFactory - ForexFactory Scraper | Economic Calendar and Forecasts

🧰 More tools

• FanDuel - FanDuel Scraper | Odds, Spreads and Player Props
• PrizePicks - PrizePicks Scraper | Player Props, Lines and Projections

📬 Support

Need something this scraper doesn't do yet? We ship features fast.

• Feature requests go straight to our backlog
• Enterprise needs? We do custom integrations and high-volume plans
• Pricing questions? Check the Monetization tab on the actor page

Response time: usually under 24 hours.

Check out our other scrapers: silentflow on Apify