We are obsessed with data quality
Since 2016, we have been building the richest database of information on all companies from the Czech, Slovak, and German markets.
When it comes to data about companies,
we don’t compromise
We make sure we consistently get the correct underlying data.
That’s why we clean, validate, link, and interpret up to 5 million records in our datasets every day.
7 mil companies
in our database
130+ thousand e-shops
in our database
assigned to company data in our database
5 mil data points
updated every day
We build our database on three principles
We invest time and money in cleaning and structuring data. That is the only way we can guarantee that our data is genuinely high quality.
Our aim is to combine the widest possible range of available data sources on companies. We also monitor many unstructured data sources and use information from them in our database.
We will always proactively propose new, innovative, and valuable interpretations of source data for our clients’ business and generate signals that our clients use in their business activities..
What data can you find in our company database?
- 53 data fields from public registers such as ARES
- 8 data fields for published contacts (email, phone) that we collect from multiple sources (web, catalogues)
- >30 data fields with details of company establishments (number, type, activity)
- >30 data fields with details of construction objects to companies (RUIAN)
- >20 selected indicators from financial statements (turnover, profit, personnel costs, etc.) and CSO (turnover)
- data from the underlying texts from company accounts (auditor, number of employees)
- >30 data fields related to taxes (VAT registration, bank accounts, etc.)
- data from ISIR - i.e. with bankruptcy and insolvency data
- data on companies from regulators (CNB, EIA, ERO, ...)
- Synthetic indicators: overall company activity, growth activity, contactability
- Information on related companies, holding structure
- International activity indicators (foreign ownership, EORI/LEI registration, etc.)
- Indicators for virtual domicile or suspicious address (algorithm for selecting inactive, shell and risky companies)
- >20 data fields on public money (subsidies, public procurement and contracts)
- an industry classification that corrects the NACE code from ARES using our own AI model
- >120 BizMachine magic labels, a special library of microsegments and company indicators for B2B sales and marketing (complementing the classic NACE classification)
- Activity categories according to records in online company catalogues (complements NACE from ARES)
- media monitoring, articles and news
- 20 data fields with information about company profiles on social networks (Facebook, Twitter, Google, LinkedIn) and their ratings
- 7 data fields with information on company websites (functionality, language versions, technology, etc.)
- >20 attributes about e-commerce (categories, size and rating of e-shops, technology, payment methods, etc.)
- >50 attributes on automotive (Vehicle registrations per company (type, manufacturer, numbers, history) & various other indicators such as electromobility)
- 9+ attributes on agro topics (Agricultural subsidies, land area, etc.)
- information on employees (number, estimated %THP) and numbers of job advertisements over time
- >40 attributes in the dataset of advertised jobs - counts by job type, industry, etc.
- >10 attributes with detailed information on individual job ads (with history from 2016)
We share insights from our data
With us, you can easily have access to data such as:
>1 mil contacts
on Czech, Slovak and German companies
4+ mil public contracts
and issued tenders
120+ pre-prepared segments
such as German companies in the Czech Republic, women-led companies, companies with an electric car, etc.
3 BizMachine indicators
overall activity, growth and contactability of the company