North Data Scraper

North Data Scraper: European company register records, officers and published financials

Type a company name or paste a North Data page, and you get the register record: registered name, legal form, court and register number, EUID, LEI, address, status, industry, corporate purpose and the registered legal representatives with their roles. 26 national registers, no account needed.

The awkward part first. Revenue and employee figures are rare. They exist only where a company is required to publish accounts, and most small European companies publish nothing. On a 260-company run of mostly small private companies, revenue was filled on 2% of rows and employees on 1%. The register fields were on every row. Buy this for the register data, and treat the financials as a bonus when they turn up.

🏷️ What North Data Scraper does

North Data pulls 26 national company registers into one site. The German Handelsregister, Austria's Firmenbuch, UK Companies House, France's Sirene, the Dutch KvK, Sweden's Bolagsverket, Spain's Registro Mercantil and the Greek GEMI are all in there, along with Israel.

Search by name, or paste company pages and ?query= search pages. Both in the same run is fine.

includeDetails is the setting that changes the run. Left on, every company page is opened and you get the full record. Turned off, you get only what the results listing shows: name, city, country, register id and status. That is much faster and it is the right choice when you are building a shortlist rather than a dataset.

Three extras are off by default because they make rows noticeably bigger. includePublications adds up to 25 register announcements per company, which is where appointments, capital changes, mergers and insolvency notices live. includeEvents adds the company page's short, dated register history. includeFinancialHistory swaps the latest-year figures for the whole year-by-year series.

📥 What you give it

{
  "searchQueries": ["Zalando SE", "Red Bull GmbH"],
  "countries": ["DE", "AT"],
  "maxItems": 50,
  "includeDetails": true
}

📤 What you get back

A real row from a run on 20 September 2026, with the full detail turned on:

{
  "ok": true,
  "name": "Zalando Stores Experiences & Clearance Solutions GmbH & Co. KG",
  "formerNames": ["Zalando Stores GmbH & Co. KG", "Zalando Outlet Stores GmbH & Co. KG", "..."],
  "legalForm": "KG",
  "status": "Active",
  "registryId": "Amtsgericht Charlottenburg (Berlin) HRA 55406 B",
  "registryLine": "District Court of Charlottenburg (Berlin) HRA 55406 B",
  "register": "District Court of Charlottenburg (Berlin)",
  "registerNumber": "HRA 55406 B",
  "northDataId": null,
  "euid": "DEF1103R.HRA55406B",
  "lei": null,
  "otherIdentifiers": [{ "source": "EUID", "label": null, "value": "DEF1103R.HRA55406B" }],
  "address": "Valeska-Gert-Str. 5, 10243 Berlin, Germany",
  "formerAddresses": [],
  "street": "Valeska-Gert-Str. 5",
  "postalCode": "10243",
  "city": "Berlin",
  "countryCode": "DE",
  "country": "Germany",
  "industry": "Renting and operating of own or leased residential real estate",
  "foundingDate": "2018-11-08",
  "corporatePurpose": "Object of the company: The management of own assets.",
  "officers": [],
  "officerCount": 0,
  "revenue": null,
  "revenueYear": null,
  "revenueFormatted": null,
  "earnings": null,
  "earningsYear": null,
  "employees": null,
  "patentsLatestYear": null,
  "patentsLatestCount": null,
  "publicationCount": 10,
  "latestPublicationDate": "2026-04-27",
  "url": "https://www.northdata.com/Zalando%20Stores%20Experiences...",
  "detailsFetched": true,
  "searchQuery": "Zalando",
  "scrapedAt": "2026-09-20T07:05:00.985Z"
}

The formerNames list and the url are cut short above. A real row carries them in full. This is what a small subsidiary looks like: register data complete, financials empty.

🧾 Reading the output

Company rows carry no charged field. The flag is only on the sample and diagnostic rows, to mark them as not real results.

Rows are written as each company page finishes, so a run that hits its timeout keeps everything already delivered.

▶️ How to run it

1. Open North Data Scraper and click Try for free. 2. Type names into Company names to search, or paste links into North Data URLs. 3. Pick Countries if you want to narrow it. 4. Set Maximum companies. Leave Open each company page on unless you only need a shortlist. 5. Click Start, then download the dataset as JSON, CSV or Excel, or read it from the Apify API.

💰 How much does it cost?

$2.55 per 1,000 companies. Flat on every Apify plan, with no volume tiers.

One billed row per company delivered. The sample row is not billed, diagnostic rows are not billed, and a search that matches nothing produces no billed rows.

💡 What people use it for

• Verifying a supplier or customer before contracting: register number, status, address and who can

sign for the company.

• Building a list of companies in one industry and country, then enriching it from the register

fields rather than guessing.

• Watching status and latestPublicationDate on a schedule to catch liquidations and insolvency

notices early.

• Pulling EUID and LEI for reconciliation against an internal system that keys on them.
• Tracing a group: formerNames and formerAddresses connect entities that have been renamed or

moved.

🚧 What it does not do

• No paywalled data. Balance sheets, profit-and-loss statements, shareholders, ownership graphs

and risk reports sit behind a North Data subscription and are not read.

• No personal contact details. Officers come back as the register publishes them, name and role.

No emails, no phone numbers, no home addresses. Person pages are rejected as input.

• About 59 results per search term is North Data's own ceiling for visitors without an account.

Split into narrower terms, by city or keyword or legal form, rather than expecting one broad term to return everything.

• Country, legal form and status are not deep filters. The countries option narrows the pool

that a term returns. It does not make North Data search further down.

• includeEvents is a short list. North Data's page showed 12 entries at most in our tests,

not a company's full register record.

• employees is a hint, not a headcount. It is read from the page text and can pick up a number

that belongs to a register announcement rather than to the company. Check it before relying on it.

• A search term that fails on its first page is reported as failed and any partial matches it

had are dropped rather than delivered. Re-run that term on its own.

• With includeDetails off, most columns are empty. That mode is a shortlist, not a record.

🧭 Which business data scraper do you need?

❓ Questions people ask

How do I get a German company's HRB number? Search the name and read registerNumber together with register. euid gives you the EU-wide identifier on top.

Which countries are covered? Austria, Belgium, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Ireland, Israel, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Spain, Sweden, Switzerland and the United Kingdom.

Can I get full accounts? No. Only the revenue and earnings figures North Data shows openly. Balance sheets are behind its subscription and are not touched.

Can I search for people? No. This is a company scraper and person pages are rejected. Officer records carry names and roles only.

How do I get more than 59 results for one term? Use several narrower terms in the same run. City names, keywords and legal form suffixes all work well as splits.

Is this legal? It reads pages North Data publishes without a login, and the underlying facts are public register records. Officer names are personal data, so GDPR applies to what you do next. Apify's write-up on scraping and the law is a good starting point, and we are not lawyers.

🆘 If something breaks

Open the Issues tab on the actor page. Send the name or URL you used and the run ID. The errorCode on the diagnostic row usually names the problem on its own.