How to find acquisition targets in Poland - a practical data guide for PE funds

Poland's company data starts with three public registers, and they're free. KRS (Krajowy Rejestr Sądowy) is the National Court Register - every legal entity except sole proprietorships, with directors, ownership and filed financials. CEIDG holds the country's sole proprietorships, around 2.5 million of them. REGON is the statistical register, useful for classification and cross-referencing. There's also CRBR, the beneficial-owners register, which matters when ownership is layered.

This layer earns its place on a specific kind of target. A lot of Polish companies are old-school - 30 years in business, barely visible online, no marketing footprint to speak of. They won't show up in a content-driven search and they're thin in commercial datasets. KRS is where you find them, because every legal entity has to be there regardless of how invisible it is on the web.

All of it is searchable through the official portal at biznes.gov.pl, by NIP, REGON, KRS number, company name or location. For a serious mapping effort you'll want programmatic access - there are APIs (Transparent Data, Kyckr and others) and scrapers that pull KRS data in bulk rather than one entity at a time.

What you get here is authoritative - legal status, registered financials, formal ownership. What you don't get is the thing you actually need next - how to reach the decision-maker directly, and which of these companies fit a niche thesis rather than a broad PKD code.

Above the registries sit commercial aggregators that pre-package the data. ALEO and rejestr.io both pull from KRS and CEIDG and add a friendlier layer - rejestr.io is particularly good at surfacing who the president or board members are, with website links attached. Bizraport is worth knowing too - Polish companies are required to file financial statements, and bizraport aggregates them, so it's one of the more reliable places to find revenue figures. HitHorizons and Global Database layer firmographic and contact data on top.

These are worth using for speed - a first-pass universe in hours rather than days, with names, presidents, website links and rough revenue already attached. They're a starting filter, not a finish line.

The trade-off is coverage and depth. The decision-maker name and website link these tools provide often cover only 20% of your list or less - for the rest, the field is simply blank. Sector tags are coarse, so a 'healthcare distribution' label won't tell you whether a company is 99% focused on your niche or just dabbles in it. And contact data, where present, skews toward general company lines rather than the owner you actually want.

M&A-specific platforms like Mergr, Crunchbase and Dealroom add a different layer - transaction history, ownership changes, who's acquisitive, who recently sold. For understanding the competitive and PE landscape around a sector, they're genuinely useful.

Their limitation for Polish niche sourcing is coverage, and it's severe. These platforms index companies that show up in deal flow, funding rounds and press - which systematically under-represents the quiet, owner-managed Polish firm that has never raised, never sold, and never appeared in a database. In a typical Polish niche, deal-platform coverage of your real target list is minimal. Those are often exactly the targets a first-mover thesis wants.

Use them to understand the market's deal dynamics and to spot acquisitive players. Don't rely on them as your primary source for the long tail of private targets - that's not what they're built to capture.

Stack all three layers and you still don't have a target list you can act on. The registries give you legal entities and financials. The aggregators give you speed and rough tags. The deal platforms give you transaction context. What none of them gives you is the combination that actually drives outreach.

Specifically - who the real decision-maker is (in owner-managed firms, the founder, who's rarely linked to the entity in any database), how to reach them directly (their number isn't public; the website lists a reception line), and whether the company genuinely fits your niche to the degree of focus your thesis requires. For succession-driven theses, you also want signals on owner age and ownership continuity, which no single source surfaces cleanly.

This gap is the actual work of target identification in Poland, and it's why a list bought from any one source is never the finished product.

Closing it means combining sources and doing the manual work on top. Start from the registries for the legal-entity backbone, layer aggregator data for what's there, cross-reference deal platforms for context - then go beyond all of them, because the companies that matter most are often the ones none of these capture well.

Two blind spots drive the extra work. The old-school firms barely exist online, so they slip through any content-driven search - KRS catches them. And many companies that are online still have no LinkedIn presence and never appear in datasets like Apollo, so a contact-database approach misses them too. The way through is a careful Google Search scrape, often run per voivodeship or per city for local operators, precisely because these businesses don't surface in a single national query. On top of that come industry-specific databases - sector associations, conference exhibitor lists, trade directories - which often hold the cleanest list of who actually operates in a niche.

Then it gets assembled. The goal is one record per target with the fields that actually drive outreach - company name, website, the decision-maker's name and contact details, a company email, size in employees, and size in revenue. The last two are frequently incomplete in every public source, and verifying them often takes a phone call. That assembly - pulling fragments from registries, aggregators, scrapes and industry sources into one clean record - is the real deliverable, not any single dataset.

Reaching the decision-maker is its own problem. Very often there's simply no way to find the owner's email - no LinkedIn profile, nothing public. You work it through a general company line or inbox, or through another employee. In smaller firms (under ~50 people) the general route usually reaches the owner; above that it gets hard, and you go in through other decision-makers instead.

Whether to build this in-house comes down to two things - language and scale. If you have a Polish-speaking analyst who can navigate KRS, read the filings, and verify owners, and your niche is small enough to work methodically, an internal effort is entirely doable. The sources are public and the method isn't secret.

It gets harder when the work has to move from identification into contact - reaching owners who don't answer unknown numbers, in Polish, with the patience and register that owner-managed firms expect. That's a different skill set from data work, and it's usually the point where funds bring in a specialist who can carry the map through to booked meetings.

Either way, the principle holds - the list is the start, not the deliverable. A target you've identified but can't reach is not yet a target.