For PE, search funds and M&A teams in DACH

Surface potential acquisition targets before they hit the market.

TargetRadar scores Austrian companies on exit-readiness using public Firmenbuch filings. Stop manually screening hundreds of filings. Start with a ranked, evidence-backed shortlist.

Get in contact See the dashboard

Deterministic scoring · No black-box ML · Every score point traceable to a public filing

Five scoring dimensions, customisable on request

Built on public Firmenbuch data

Minutes, not hours, to a shortlist

Scales to any company set you define

The problem

Manual deal sourcing doesn't scale.

Your team is reading Firmenbuch filings by hand, building spreadsheets of "interesting candidates", and quietly missing the ones that are actually about to transact.

Hours per week per analyst on screening
Subjective "looks promising" calls without an audit trail
The same patterns rediscovered every quarter
Targets land on the market before you spot them

The deal funnel

800 → 50 → 1

From hundreds of candidates to a handful of qualified targets to one closed deal. That's the realistic conversion in lower mid-market M&A. TargetRadar removes the first step from your hands so your week goes to the candidates that matter.

Who it's for

Anyone who works with Austrian company data.

If you spend time pulling, comparing or interpreting Firmenbuch filings, TargetRadar saves you that time. Whether you're hunting deals, advising clients, or mapping a market.

Investors

PE, search funds, family offices

Source proprietary deals directly from public data. Spot succession-driven exits and ownership transitions before they're packaged by an advisor.

Advisors

M&A boutiques, consultants, lawyers

Pitch with confidence. Give clients a ranked, evidence-backed list of targets in their sector with every score point linked back to a real filing.

Researchers

Strategy and market analysts

Build sector views, watchlists, competitor maps. TargetRadar turns thousands of raw filings into a clean, queryable database in seconds.

How it works

Raw filings in. Ranked shortlist out.

Collect

Fetch annual filings from JustizOnline Firmenbuch. Fully automated.

Parse & consolidate

Extract financial positions, signatories and ownership history into a per-company timeseries.

Score

Compute the deterministic 0 to 100 Exit-Window Score across five weighted dimensions.

Explore

Filter, rank, drill in. Every score point links to the specific filing fact behind it.

The score

Five weighted dimensions. Zero black boxes.

Every point traces to a public filing: owner age, founder name match, shareholder change, equity ratio, harvesting pattern. Calibrated against research on what actually predicts SME exits.

35%

Exit Likelihood

Owner intent and ownership-transition signals. The most direct exit indicators.

Owner age profile (Geschäftsführer, Vorstand)
Founder name match in company name
Key-person concentration risk
Management stability over years
Gesellschafter-Wechsel, actual ownership transitions

25%

Business Quality

Sector-neutral measures of financial health. Size is a filter, not a score.

Profitability consistency (last 5 years)
Equity ratio
Multi-year revenue or asset growth
Leverage (FK/EK)

20%

Timing Signals

Behavioural patterns visible in the filings, the preparing-to-exit footprints.

Sustained Sachanlagen decline
Harvesting: revenue up, capex down

10%

Deal Feasibility

Whether a transaction would be operationally clean.

Rechtsform: GmbH transfers cleanest
Shareholder structure: single owner cleanest
No negative signals (insolvency, sustained losses)

10%

Market Context

Sector classification, today heuristic, NACE-backed soon.

M&A-active, stable or structurally challenged sectors
Honest "not classifiable" flag when uncertain

Questions

What you're probably wondering.

Where does the data come from?

From the Austrian commercial register (Firmenbuch), the same public filings every Austrian company is required to submit annually. We add ownership-structure data from licensed sources. Nothing comes from insider channels or non-public information.

How is the scoring different from "AI-driven" tools?

It's deterministic. No machine learning, no training set, no opaque model. Every point in the 0 to 100 score maps to a specific fact in a specific filing year. You can show a portfolio committee exactly why a company scored what it did, and re-running on the same data always produces the same number.

Are companies on the list actually for sale?

We don't claim they are. TargetRadar measures signal strength: how many independent indicators of an approaching transition the filings show. A "Very Strong" score means the public evidence is stacking up. The conversation still has to happen. Score is a priority filter, not a "for sale" sign.

What does it cost?

Get in contact for pricing. Pricing depends on team size and the company set you want covered.

How is this different from Compass, Creditreform or S&P Capital IQ?

Those are data warehouses. They show you what's there. TargetRadar is a screening engine on top of a similar data foundation, optimised for the specific question "which of these companies look ready to transact?". We're not replacing your data subscription. We're replacing the spreadsheet your analyst builds from it.

Is what you're doing legal?

The Firmenbuch is public by law. Our analysis builds entirely on publicly disclosed filings. No insider data, no PII processing beyond what the Firmenbuch itself publishes, and licensed sources for everything else.

What's the coverage?

For demonstration purposes we currently score a few hundred Austrian companies across major sectors. The pipeline is fully scalable: tell us the company set you care about (by sector, region, size band, or a custom list) and we extend coverage to match.