North Data Scraper: European Company Registry Data in 2026

Registry data is B2B’s ground truth

Self-reported company profiles lie by omission: inflated headcounts, vague addresses, dead entities that still look alive. Official registries don’t. Legal names, registration numbers, officers and status come from government sources — and North Data aggregates them across Europe: Germany’s Handelsregister, the UK’s Companies House, France’s Siren, Belgium’s KBO, the Netherlands’ KvK, Italy’s REA, Spain’s Registro Mercantil and the Nordic registries.

It’s the rare place where a German GmbH and a UK Ltd sit side by side in comparable form. Extracting it in bulk turns compliance-grade data into an operational asset.

What you can extract

Per company, normalized into one schema:

• Legal name and North Data ID
• Registry record — court, number, unique key
• Full address with coordinates
• Officers — name, role, appointment date
• Founding date and status
• Industry classification
• Corporate events and history
• Corporate purpose

The technical challenge

The hard part isn’t volume — it’s heterogeneity. Registry records arrive in different languages, formats and legal conventions; a naive scraper gives you seven incompatible datasets instead of one. What matters:

• Normalization into a single schema across countries.
• Deduplication by country-prefixed registry key, so the same entity never appears twice.
• Precise matching — company-name searches must route exact matches straight to the right profile. The parsing itself is classic web scraping; see our notes on when APIs beat scraping for the general trade-off.

DIY or a ready-made Actor?

Our North Data Scraper on Apify does the normalization work for you: feed it company names (up to 20 matches each) or North Data URLs, optionally include officers, and get one consistent schema back across all registries. Pay-per-result at about $0.008 per company profile.

A practical workflow

1. Input your list — prospect names from your CRM, or search queries by market.
2. Extract and normalize — one run returns registry-grade records with officers and events.
3. Match and enrich — join on registry keys against your existing data; add commercial signals from automated lead generation sources.
4. Operationalize — feed KYB checks, due diligence files or sales territory planning.

Use cases that pay off

• Due diligence — verify names, numbers, status and officers before signing.
• KYB and compliance — a normalized European feed for onboarding workflows.
• Lead enrichment — official firmographics on top of your prospect lists.
• Market mapping — company datasets by industry and region, from registry sources.

The legal boundaries

• Registry data is public by design — publication is its legal purpose; extraction for analysis is on firm ground.
• Officers are people — names and appointments are personal data under GDPR; process them with a lawful basis and minimize retention.
• Respect the aggregator — reasonable request rates keep your access sustainable.

Getting started

Run the North Data Scraper on your top 50 accounts and diff the results against your CRM — the corrections usually justify the exercise on day one. For the commercial layer on top, pair it with the Store Leads scraper or ImportYeti scraper. Bigger KYB or enrichment pipelines are what we build at SilentFlow.