Home Who we serve Search funds
Who we serve — search funds & self-funded searchers

Two years. One company. A list nobody else is calling.

Your committed capital buys a fixed number of months, and the shared databases sell the same export to every searcher in your cohort. We screen the entire active web against your thesis in the first weeks — so the rest of the search is spent calling, not compiling.

100M+classified domains screened
~17,300live operators from one 25,000-domain triage
1 in 10keyword-perfect names already group-owned
15evidence-backed signals per company
Data trusted in production 300+ enterprise organisations One of Europe's largest telecom operators Adtech & cybersecurity platforms A leading airline metasearch
The economics you live with

The searcher's clock only runs one way

A search is a fixed budget divided by a monthly burn. Every sourcing month that produces recycled names is a month subtracted from the only outcome that matters — one closed acquisition.

1

Months 0–2Raise, write, promise

You raise search capital on a thesis and a sourcing story. Investors back the story partly because you promised proprietary deal flow — companies they will not see in a banker's process.

2

Months 2–6The export honeymoon

The licensed database yields a few hundred filtered names. Sequences go out, interns enrich rows, response rates look survivable. It feels like a machine. It is a queue.

3

Months 6–12List fatigue

The queue empties. The same polished mid-size companies every profile database indexes have now heard from you, your cohort, and three consolidators. Reply quality drops before reply volume does.

4

Months 12–18Broker gravity

Intermediated deal flow fills the calendar because it is available, not because it is right. Whatever arrives through a broker is, by definition, not proprietary — and rarely priced as if it were.

5

Months 18–24Pipeline arithmetic

Now the funnel math is public: owners contacted, conversations held, IOIs signed. If the top of the funnel was never a census, no amount of cadence discipline fixes the denominator.

Weeks 1–3Where we change the clock

We deliver the full universe for your thesis — every qualifying company on the active web, scored and evidenced — inside the first month. The grind still happens. It just starts from everyone, not from an export.

The structural problem

"Proprietary" is a property of the starting pool

The shared-database trap

Every searcher in your cohort licensed the same tools, applied the same industry filters, and exported overlapping lists. The companies inside are real — and thoroughly contacted.

Profile databases index what their crawlers and analysts found: the visible, the funded, the polished. Your thesis lives mostly outside that index, in businesses whose websites say "trusted since 1987", not "platform".

Start from the whole web

We start from 100M+ classified domains — 24.7M in business and finance alone, organized across 700+ categories — and read every candidate site against your thesis as you wrote it.

Not code tables standing in for the thesis. The thesis itself, applied by LLM analysis with a verbatim quote and source URL behind every inclusion and every exclusion.

The uncomfortable synthesis

If your list started where everyone else's list started, it was never proprietary — however good your outreach. A searcher's real edge is a denominator: knowing, with evidence, that you are working the entire population of qualifying companies, most of which no shared export has ever surfaced.

The method, applied to a search

Two passes. Fifteen signals. Zero unverifiable claims.

Pass one is triage: separating live operating companies from directories, parked domains, and resellers of record. In one industrial category, a 25,000-domain US-focused triage left roughly 17,300 genuine operators.

Pass two reads the survivors in depth — fifteen structured signals per company, from ownership language to certifications to service-model classification, each carrying the exact sentence that supports it. The method page documents every signal.

Scoring is opinionated on purpose: Mandate Fit carries 70%, Outreach Suitability 20%, Transition Context 10% — and group ownership zeroes a company out entirely, because a subsidiary is not a lower-priority target. It is not a target.

What a scored row looks like

Target M-01 — top fit. "a fourth-generation, family-owned precision CNC machining company" — AS9100D, ITAR, named president, no group language anywhere on the site.
Hidden M-02 — keyword-missed fit. "family-built, American-owned since 1965" — machining depth two pages deep; absent from keyword-driven indexes.
Excluded M-01 — documented exclusion. "a wholly owned subsidiary" — keyword-perfect homepage, already consolidated. Scored zero, with the quote.
Before the screen runs

Six properties of a thesis the web can actually answer

The screen is only as good as the question. These are the six things we push searchers to pin down in the intake session — most take one working call.

01

Activity, not label

Define the subsector by what companies do — "installs and services industrial water systems" — not by an industry code. Websites describe activities; codes describe filings.

02

Geography with a reason

A radius, a set of states, or a density argument. We extract stated branch locations and service areas, so the universe can be sorted against where you will actually live and operate.

03

Independence, explicitly

Nearly every searcher wants an independent company; few write it down. We make it a hard gate: any group, platform, or brand-family language zeroes the score, with the quote attached.

04

Revenue character

Service contracts, maintenance programs, consumables — the visible language of repeat business. If recurring character matters to your model, it becomes a scored signal, not a diligence surprise.

05

Hard disqualifiers

Residential mix, pure distribution, franchise systems — whatever your model cannot digest. Disqualifiers written into the thesis save hundreds of research hours downstream.

06

Verifiable evidence

Every criterion must be answerable from what companies publish. We refuse thesis terms that require guessing — that discipline is why the positives are trustworthy. See our standards.

The denominator

Numbers from a real specimen run

One industrial category, screened end to end. This is what a counted universe looks like before anyone writes a single email.

0domains in the category, globally
0live US operators after triage
0eligible independents in one subvertical
0signals extracted per company

Ten subverticals from the same category, each with its count of eligible independent US companies — the kind of denominators searchers put in investor updates.

Precision machining 702 Equipment repair 545 Automation integration 534 Material handling 513 Compressed air 276 Calibration & testing 254 Water treatment 221 Boiler & steam 172 Filtration 109 Surface finishing 93
Signal deep-dive

The six signals that carry a search

All fifteen ship with every row. For a searcher planning two years of owner conversations, these six do most of the ranking work.

Founder & family association

Explicit language only — "second generation", "founder-led", "family-owned" — never inferred. Roughly half of confirmed industrial fits carried it. For a searcher, this shapes the first letter you write, because these owners answer stewardship, not slideware.

Operating history & independence

Stated founding year, decades in operation, independence language. Long-established, founder-associated businesses with an identifiable decision-maker and a limited visible leadership bench are the classic search profile — documented strictly from what each company publishes about itself.

Roll-up readiness (the zero-out)

The signal that saves your calendar. About one in ten keyword-perfect candidates in our runs was already inside a group — visible on its own site, stale in profile databases. Each is excluded with the disqualifying sentence quoted.

Recurring-offering indicators

Maintenance agreements, scheduled programs, consumables streams. Your investors will ask about revenue quality at the first update; this signal means you walk into every owner call already knowing what the company says about its own repeat business.

Leadership bench depth

How many principals are actually named, and whether visible management extends beyond one or two people. It calibrates the transition you would be stepping into — a real consideration when the plan is you, in the seat, on day one.

Website activity trajectory

Most recent dated content, news cadence, posting rhythm. A dormant site is not a verdict, but it changes outreach order — and in a two-year search, sequencing the population well is half the return on the data.

A worked example

Anatomy of the 20-company specimen

Every engagement starts with a specimen you can audit: 8 top fits, 5 keyword-missed fits, 5 documented exclusions, 2 insufficient-evidence flags. The machining specimen is public.

Top fits

8

Confirmed matches to the written thesis, ranked by score, each with certifications and ownership language captured as exact claim text.

"a fourth-generation, family-owned precision CNC machining company" — AS9100D, ITAR, president named on the site.

Keyword-missed fits

5

Real qualifiers whose homepages lack the category's obvious vocabulary. A fifth or more of confirmed fits carry this profile — the closest thing to genuinely uncontacted deal flow a searcher can buy.

"family-built, American-owned since 1965" — the machining story starts two clicks deep.

Documented exclusions

5

Keyword-perfect candidates we removed, with reasons quoted: subsidiaries, brand families, one company announcing its own acquirer on its news page.

An exclusion log is what makes the inclusions credible — to you, and to the investors reading your updates.

Insufficient evidence

2

Companies whose sites do not answer the thesis either way. We flag them instead of guessing — a small honesty that tells you exactly how much manual follow-up the tail requires.

Vendors who never say "we don't know" are telling you something about their positives.

The number searchers remember: roughly one in ten keyword-perfect candidates was already group-owned — companies that would have absorbed a research week and a first call each, working from an export alone.

The honest comparison

Shared databases vs. a full-web universe

Profile databases are good at what they index. The question is whether what they index is where your search will be won.

DimensionShared profile databasesFull-web thesis screening
Starting poolCompanies their crawlers found100M+ domains — the active web itself
Thesis fidelityIndustry codes and keyword filtersYour thesis text, read against every site
Long-tail coverageThins out below the polished mid-marketBuilt for 10–60-person operators
Evidence per claimProfile fields of uncertain vintageVerbatim quote + source URL, every row
Exclusion logNone — you discover dead ends yourselfEvery removal documented with its reason
Who else works the listEvery subscriber with similar filtersBuilt once, for your thesis alone
Cost modelAnnual seat licensesProject pricing from €4,900

Keep a database seat for…

Contact enrichment, firmographic lookups on companies you already know, and coverage of large, well-documented targets in banked processes.

Use the universe for…

The census itself: who exists, who is independent, who fits, who is already owned — with evidence your investors can audit. Then run a gap analysis against your current pipeline.

Pricing logic for a search budget

Priced like a project, because a search is one

A search fund does not need another annual license. It needs the population, once, done properly — then a way to re-cut it as the thesis sharpens after the first fifty conversations.

Custom ICP re-runs are included: tighten geography, add a certification gate, exclude a service mix, and the scoring re-runs across the whole universe at no additional cost. The lens adjusts; the asset stays.

Compare it to the alternative you were about to choose: months of intern hours assembling a list that still starts from the same shared index. Full detail on the pricing page, and the search fund use case shows the deliverable anatomy.

Proof project from €4,900

One subvertical, screened end to end, specimen format. The cheapest way to test whether your thesis survives contact with the full web — most searchers start here.

Full universe + deep shortlist from €9,900

The core searcher buy: the complete evidenced universe for the thesis, scored and ranked, with the shortlist your outreach starts from. Re-runs included.

Annual monitoring from €18,000

Scheduled re-screens and structured deltas per thesis. Most single-thesis searches will not need it — it earns its keep for accelerators and funds running several searchers on adjacent theses.

Say it plainly

Where this works — and where it will not

A vendor that cannot describe its bad fits is asking you to find them for it. Ours are below, in writing.

A strong fit if you are…

  • Searching in fragmented B2B services, niche manufacturing, or industrial trades — say, precision machining — where the long tail is the market.
  • Able to state your thesis in plain language — activities, geography, disqualifiers — even loosely; the intake call sharpens it.
  • Planning to own outreach yourself and wanting every calling hour aimed at verified, independent, uncontacted companies.
  • Reporting to investors who ask "how big is the population?" and deserve a counted, evidenced answer.

Not the right buy if you…

  • Source exclusively through bankers and brokers — we map open water, not auction calendars.
  • Need owner intent flags. No website signal supports them, so we refuse to sell them; our standards explain why.
  • Want financial figures appended to each row. Websites do not publish them, and we do not guess.
  • Search in consumer-captive verticals we exclude on principle — the excluded list is published, not negotiated.
Searcher FAQ

Questions searchers actually ask us

How is this different from the database seats my cohort already shares?
The difference is the starting pool. A profile database can only rank what it already indexed — a population skewed toward size, polish, and funding events, worked by every subscriber. We start from 100M+ classified domains and read each candidate against your thesis text, which is why a fifth or more of confirmed fits in our runs never appear in keyword-driven indexes at all. You keep the database for enrichment; the universe replaces it as the census.
Can you tell me which owners are open to selling?
No — and we would distrust any vendor who says yes. No website signal supports a claim about willingness to transact, so we never make one. What we do document, strictly from published text, is transition context: founder-associated, long-established, independently positioned businesses with an identifiable decision-maker and limited visible leadership bench. That context shapes outreach; it does not predict outcomes.
What exactly arrives, and in what format?
A structured CSV built for CRM import: one row per company, fifteen signals, three scores, a verbatim evidence quote and source URL for every material claim, plus the exclusion log and insufficient-evidence flags. Working views come pre-cut — top-scored uncontacted, founder-associated, keyword-missed. The live sample shows the real column structure.
My thesis will change after the first hundred calls. What then?
That is the expected path, and it is why re-runs are included rather than sold back to you. When you learn that municipal contracts matter more than fleet size, or that one certification is non-negotiable, we re-score the existing universe against the revised ICP at no additional cost. The universe is the durable asset; the scoring is a lens you keep adjusting as the search teaches you.
How long before I can start calling?
A same-day specimen before you commit anything, then two to three weeks for a first complete, analyst-verified universe on most theses. Searchers typically run their existing sequences in parallel and cut over to the scored list as soon as it lands — no dead time, and the first proprietary conversations usually start within the month.
Is my thesis kept confidential from other searchers?
Yes. Each engagement is a separate build against your written thesis, and we do not resell, pool, or recycle client universes — the shared-list dynamic is precisely the problem this replaces. Anonymized aggregate figures like the ones on this page are the only thing that ever becomes public, and never in a form that identifies a thesis or a target.
What we refuse to sell: no owner-intent flags, no financial guesses, no personal profiling of owners, no consumer-captive verticals. The full list, and the reasoning, is public — read our standards.

Spend your search calling, not compiling

Send one email with a sentence about your thesis. You get the specimen report the same day — every company scored and ranked with full signal transcripts, including the ones we refused to include. Then decide.