# Northdata Company Scraper (`silentflow/northdata-scraper`) Actor Scrape Northdata.com for European company profiles. Pull registry, officers, address, foundingDate, industry, status, events and corporate purpose from UK Companies House, Siren, Handelsregister, KBO, KvK and more. Search by name or load specific URLs. Per-result pricing, proxies included. - **URL**: https://apify.com/silentflow/northdata-scraper.md - **Developed by:** [SilentFlow](https://apify.com/silentflow) (community) - **Categories:** Lead generation, SEO tools, Other - **Features:** Limited permissions - **Stats:** 144 total users, 19 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: No ratings yet ## Pricing from $6.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Northdata Scraper **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 ![How it works](https://api.apify.com/v2/key-value-stores/OXaZXulzN2QxHCEyw/records/how-it-works-v1.png) ### ✨ 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? - πŸ’° **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. - πŸ“ˆ **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. - πŸͺͺ **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. - πŸ•ΈοΈ **Related companies.** Acquisitions, mergers, break-ups, control agreements and shareholdings, each with its date, to map a holding structure from one profile. - πŸ‘₯ **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. - πŸ”— **Industry breadcrumbs included.** Every record carries its NACE-style industry classification path, so you can segment leads by sector without a separate lookup. - πŸ›‘ **High reliability.** Profiles served by Northdata sometimes shift between languages and locales. Output is normalised regardless of source language. - πŸ“¦ **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 | ### πŸ“₯ 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`. ### πŸ“Š 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 ```json { "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 ```json { "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": "KΓΆnigslutter" }, "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 ```json { "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" } ``` ### πŸ—‚οΈ 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 | ### πŸš€ Examples #### Look up one company by name ```json { "searchQueries": ["Siemens Energy"], "maxItems": 5 } ``` #### Build a 200-row enrichment of UK aerospace players ```json { "searchQueries": ["aerospace"], "maxItems": 200, "includeOfficers": true } ``` #### Pull a single profile by direct URL ```json { "startUrls": [ { "url": "https://www.northdata.com/Rolls-Royce%20plc,%20London/Companies%20House%2001003142" } ] } ``` #### Get the list of directors for ten target companies ```json { "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 ```json { "searchQueries": ["Robert Bosch", "Siemens", "Continental"], "country": "DE", "maxResultsPerQuery": 5, "maxItems": 15 } ``` #### Map a director's mandates ```json { "searchQueries": ["Oliver Blume"], "resultType": "people", "maxItems": 10 } ``` #### Listing-only mode for a fast first pass ```json { "searchQueries": ["software", "fintech", "logistics"], "maxItems": 90, "includeOfficers": false } ``` ### πŸ€– Copy to your AI assistant Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor. ```text 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) β†’ inputSchema, actorDefinition.storages.dataset, readme. Get token: https://console.apify.com/account/integrations ``` ### πŸ’» Integrations #### Enrich a list of leads in Python ```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 ```javascript 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 ```bash curl "https://api.apify.com/v2/datasets/DATASET_ID/items?format=csv&token=YOUR_APIFY_TOKEN" \ > northdata_leads.csv ``` ### πŸ“ˆ 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. ### πŸ’Ύ 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. ### πŸ’‘ 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. ### βš–οΈ 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. 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[PagesJaunes Business Scraper](https://apify.com/silentflow/pagesjaunes-scraper-ppr) - **SEC** - [SEC Scraper | EDGAR Filings and Company Data](https://apify.com/silentflow/sec-scraper) - **SIRET** - [SIRET Company Enricher](https://apify.com/silentflow/siret-enricher-ppr) - **SpyFu** - [SpyFu Scraper | SEO, PPC and Competitor Data](https://apify.com/silentflow/spyfu-scraper) - **Sunbiz** - [Sunbiz Companies Scraper | New Florida Business Leads](https://apify.com/silentflow/sunbiz-companies-scraper) - **Sunbiz** - [Sunbiz Scraper | Florida Companies and Officers](https://apify.com/silentflow/sunbiz-scraper) - **USPTO** - [USPTO Scraper | Trademark Search and Status](https://apify.com/silentflow/uspto-scraper) - **Clutch** - [Clutch Scraper | Agencies, Reviews, Ratings, Services](https://apify.com/silentflow/clutch-scraper) - **Clutch Agency** - [Clutch Agency Scraper](https://apify.com/silentflow/clutch-scraper-ppe) - **SIRET French** - [SIRET French Company Enricher](https://apify.com/silentflow/siret-enricher) - **ThomasNet Suppliers** - [ThomasNet Suppliers Scraper](https://apify.com/silentflow/thomasnet-scraper) - **ZocDoc** - [ZocDoc Scraper](https://apify.com/silentflow/zocdoc-scraper) **πŸ”Ž SEO** - **Similarweb** - [Similarweb Scraper | Website Traffic, Rankings and Competitors](https://apify.com/silentflow/similarweb-scraper) - **Apple** - [Apple Reviews Scraper | App Store Reviews and Ratings](https://apify.com/silentflow/apple-reviews-scraper) - **Apple** - [Apple Scraper | App Store Apps, Ratings and Charts](https://apify.com/silentflow/apple-scraper) - **Bing** - [Bing Enricher Scraper | Mobile Friendly Test and Indexing](https://apify.com/silentflow/bing-enricher-scraper) - **Google News** - [Google News Scraper](https://apify.com/silentflow/google-news-scraper) - **Scribd** - [Scribd Scraper | Documents, Authors and Views](https://apify.com/silentflow/scribd-scraper) **πŸ“ˆ Marketing** - **Douyin** - [Douyin Transcript Scraper | Subtitles and Speech to Text](https://apify.com/silentflow/douyin-transcript-scraper) **🎬 Video** - **Pexels** - [Pexels Scraper | Photos, Videos and Download Stats](https://apify.com/silentflow/pexels-scraper) **πŸ“° News** - **ForexFactory** - [ForexFactory Scraper | Economic Calendar and Forecasts](https://apify.com/silentflow/forexfactory-scraper) **🧰 More tools** - **FanDuel** - [FanDuel Scraper | Odds, Spreads and Player Props](https://apify.com/silentflow/fanduel-scraper) - **PrizePicks** - [PrizePicks Scraper | Player Props, Lines and Projections](https://apify.com/silentflow/prizepicks-scraper) ### πŸ“¬ 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](https://apify.com/silentflow) # Actor input Schema ## `searchQueries` (type: `array`): Company names, director names, keywords or register numbers, typed as on Northdata: Volkswagen AG, Maschinenbau, HRB 100484, Oliver Blume. Each query reads up to 45 matches, the most Northdata lists for one search; a unique name opens the company directly. Run several queries to build a longer list. ## `startUrls` (type: `array`): Northdata company or person profile links (https://www.northdata.com/Volkswagen+AG,+Wolfsburg/HRB+100484) or search result links. A profile link is always delivered as is; a search link is read page after page, like a query. ## `country` (type: `string`): Keep only companies and people registered in this country, so a common name like BMW does not bring back French or Ukrainian homonyms. Pick it, or type its code (de, deu) or its English name. Leave empty to search every country. Each query still reads at most 45 matches, so a narrow country can return fewer rows. ## `resultType` (type: `string`): What a search keeps. Companies returns registered businesses. People returns directors, managers and shareholders, each with the companies they are tied to and their profile links: search a name like Oliver Blume to map someone's mandates. Companies and people keeps both, each row marked by recordType. ## `maxItems` (type: `integer`): Stop after this many rows across all queries and links. A run of 46 full company profiles takes under 30 seconds. ## `maxResultsPerQuery` (type: `integer`): Cap each query on its own, so the first name of a list does not use up Max results before the next ones run: 5 gives the five best matches of every company you look up. Leave empty to take every match, up to 45 per query. ## `includeOfficers` (type: `boolean`): Open every company's Northdata page for the fields only the page shows: officers with appointment dates, latest revenue, earnings, employees, total assets and equity, the year-by-year financial history with its source, the balance sheet lines, LEI and national identifiers (Siren, Companies House, tickers), founding date, industry codes, corporate purpose, register events, publications and related companies (acquisitions, mergers, control, shareholdings). For people, the companies they are tied to with their links. Figures show where Northdata publishes them for free, most often for listed and German companies. Turn it off for a fast list of names, places and register numbers. ## `debugMode` (type: `boolean`): Write detailed progress to the run log. ## Actor input object example ```json { "searchQueries": [ "Siemens Energy", "Heineken NV", "Robert Bosch GmbH" ], "startUrls": [], "resultType": "companies", "maxItems": 100, "includeOfficers": true, "debugMode": false } ``` # Actor output Schema ## `results` (type: `string`): Name, registry, city, country, revenue, employees, status and Northdata link of every row. ## `financials` (type: `string`): Latest revenue, earnings, employees, total assets, equity, currency, financial year and LEI of every company. ## `people` (type: `string`): Directors and officers found by a People search, with the companies they are tied to. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQueries": [ "Siemens Energy", "Heineken NV", "Robert Bosch GmbH" ], "startUrls": [] }; // Run the Actor and wait for it to finish const run = await client.actor("silentflow/northdata-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchQueries": [ "Siemens Energy", "Heineken NV", "Robert Bosch GmbH", ], "startUrls": [], } # Run the Actor and wait for it to finish run = client.actor("silentflow/northdata-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchQueries": [ "Siemens Energy", "Heineken NV", "Robert Bosch GmbH" ], "startUrls": [] }' | apify call silentflow/northdata-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,silentflow/northdata-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/NPFgqJahwiGTjGmdF/builds/4CUxTQ0ZQOrrxf09v/openapi.json