Use case · Search funds

A target list as complete as your search deserves

Your fund has one thesis and a finite clock. We screen the entire active web against that thesis — every eligible company in the niche, each with verbatim evidence, none recycled from another searcher's list.

100M+Classified domains screened
1 in 10Keyword-perfect targets already group-owned
~50%Confirmed fits with explicit founder or family evidence
€4,900Proof project, from
300+ enterprise organisations run on our data
Incl. one of Europe's largest telecom operators
A leading airline metasearch
Adtech & cybersecurity platforms
The constraint

A search is an arithmetic problem before it is anything else

Most funds budget roughly twenty-four months. Subtract diligence and closing, and the window for finding your company is shorter than it looks on day one.

~24Months of committed search capital
1Company you will actually buy
100sOwner conversations to get there
93–702Eligible independents per industrial niche we've measured

In the niches we have screened end-to-end, the entire eligible universe of independent US companies runs from 702 shops in precision machining down to 93 in surface finishing. Small numbers change strategy.

Why it matters: when the whole pond holds a few hundred fish, every name you never learn about — and every letter sent to a company that was quietly acquired years ago — is a measurable share of your search burned.

The uncomfortable arithmetic: a searcher who mails 60% of a niche is not running a 60% search. The best-fit companies cluster in the unmailed tail precisely because harder-to-find businesses get less competing mail. Coverage is not a vanity metric; it is where proprietary deals come from.

Two ways to build the list

The recycled export versus the census

What most searchers start with

A profile-based database export, filtered by industry code and headcount — often the same export the last three searchers in the niche pulled.

  • Built from directories, so it only holds companies someone already indexed
  • Industry codes miss specialists whose homepage skips the obvious keywords
  • No evidence trail — you discover the roll-up ownership on the first call

What a full-web census does instead

We start from 100M+ classified domains — effectively the whole active web — and read each candidate site against your written thesis.

  • Coverage is the entire category, not the indexed fraction of it
  • LLM analysis reads what the site says, not what a keyword filter guesses
  • Every inclusion and every exclusion ships with verbatim evidence

The practical difference

A fifth or more of confirmed fits in our specimen runs never used the category's obvious homepage keywords. Those companies do not exist in keyword-driven exports — yet they answer cold outreach like anyone else. Find them first, and you are the only buyer in the room.

Method, applied to your thesis

From written thesis to scored universe in five passes

The two-pass architecture spends cheap analysis broadly, then expensive analysis narrowly.

Thesis intake

Your acquisition criteria, written down and agreed — subsector, geography, model.

Category cut

From 100M+ domains to the candidate set — one industrial category alone held 367,478.

Triage pass

A 25,000-domain US triage resolved to ~17,300 live operating companies.

Deep extraction

Full-site reading against 15 signals, quoting the site verbatim for each.

Scored delivery

Mandate Fit 70%, Outreach Suitability 20%, Transition Context 10%.

The denominator

Numbers from real runs, not a brochure

These figures come from screening work we have actually delivered — the same pipeline your thesis would run through.

0Classified domains in the universe
0Business & finance sites among them
0Industry categories maintained
0Domains in one industrial category alone

The category cut is the honest denominator behind every count we quote. When we say a niche holds 254 eligible independent calibration and testing companies, that number survives an IC's "compared to what?" — see the specimen report.

Evidence discipline

The six signals that matter most in a search

Our framework extracts fifteen signals per company, every one grounded in a quote from the company's own site. For a searcher planning years of personal involvement in whatever they buy, these six carry the most weight.

01

Founder-led / family-led association

Explicit founder or family language on the site — "second generation", "family-owned" — never inferred. Roughly half of confirmed industrial fits carry it, and it shapes every first conversation.

02

Visible leadership bench depth

How many principals the site actually names. A one-name bench means the operator you back is replacing the whole visible leadership — priced into your plan, or a surprise later.

03

Operating history & independence

Stated founding year and independence language. Long-established shops with continued independence are the classic search profile, and the site usually says so in its own words.

04

Group ownership — the disqualifier

Signs a company already belongs to a consolidator. One in ten keyword-perfect candidates fails here; the score zeroes out and the exclusion is documented with the quote that proves it.

05

Recurring-offering indicators

Service contracts, maintenance agreements, scheduled programs, consumables — the visible language of repeat revenue that a first-time CEO can stand on while learning the business.

06

Compliance & certifications

Explicit claims only — ISO 9001, AS9100, ITAR, UL 508A, ISO/IEC 17025 — captured as exact claim text. Certifications are moats, and they are checkable in diligence.

A worked niche

What the precision machining run actually surfaced

From 702 eligible independent US shops, the specimen shortlist documents 8 top fits, 5 keyword-missed fits, 5 documented exclusions and 2 insufficient-evidence flags. Four rows, anonymized:

Target M-01

Top fit

Massachusetts, 58,000 sq ft facility. AS9100D, ITAR and CMMC Level 2 — each captured as exact claim text.

"…a fourth-generation, family-owned precision CNC machining company"— Industries page · 15/15 evidence snippets verified against site text

Target M-02

Top fit

Ohio, ISO 13485. Operating for more than eighty years with visible generational continuity on its history page.

"the company was founded in 1942 by the founder"— History page · verified against site text

Hidden fit M-02

Keyword-missed

CNC machining for defense, aerospace and medical-device customers — but the homepage never uses the category's obvious keywords.

Keyword-driven databases would likely miss it. Full-site reading did not.

Excluded M-02

Documented exclusion

A keyword-perfect contract machining company — excluded as already part of a group, with the acquisition statement quoted in the deliverable.

That is one letter you never send, and one IC question you can answer before it is asked.

Note on anonymization: client deliverables carry the real company names, verbatim evidence snippets and source URLs. On the public site, specimens are anonymized — the specimen report shows the full format.
Decision framework

Three sourcing bases, compared honestly

What a searcher needsBroker / intermediary listsProfile-based databasesFull-web screening
Covers companies nobody indexed yetOnly marketed dealsOnly the indexed fractionStarts from the whole active web
Finds fits without obvious keywordsNot applicableKeyword and code drivenA fifth+ of fits surfaced this way
Flags group-owned companies upfrontRarelyOwnership data lags1-in-10 exclusion rate, documented
Proprietary to your searchShown to every buyerSame export for every subscriberRun against your thesis alone
Evidence you can re-verifySeller-providedProfile fields, source unclearVerbatim quotes + source URLs

Brokered processes and databases both have their place — we use category data ourselves. The claim is narrower: for proprietary outreach in a defined niche, the census wins on coverage and evidence.

Niches we have already counted, end to end

Ten industrial-services subverticals from one full US run, each figure the count of eligible independent companies after triage, deep extraction and group-ownership exclusions. If your thesis touches one of these, part of your denominator already exists.

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
What this does not do

Read the limitations before you buy the coverage

A tool you trust on the way in should be honest about its edges. Ours has four.

No intent detection. We never claim to know which owners will take your call. No website signal supports that claim, and vendors who sell it are guessing — see our standards.
No financials. Company websites do not publish reliable financial figures, so we do not estimate them. Your outreach and diligence establish the economics; our job is making sure you talk to the whole niche.
Websites lag reality. Evidence is what a company publishes about itself. A shop acquired last month may not say so yet; a stale site can understate a growing business. We quote sources so you can re-check.
Thin sites yield thin evidence. In the specimen run, 2 of 20 shortlisted companies were flagged insufficient-evidence rather than force-scored. We would rather hand you an honest flag than a confident guess.
Into your process

Built to feed a searcher's actual week

The deliverable is a working file, not a PDF to admire. Scores sort your outreach tiers; evidence snippets become the first line of a letter that proves you did the reading.

Owners answer specifics. "I noticed you've held UL 508A certification since 2011" outperforms any template — and the quote is sitting in the row next to the score.

  • CSV/Sheets import with stable IDs for your CRM of choice
  • Score columns to build tiered outreach waves in minutes
  • Evidence text ready to quote in personalized first lines
  • Documented exclusions, so wave two never mails a roll-up

A sourcing week on the census

Monday. Sort by Mandate Fit; pull the next 25 names above your threshold.
Tuesday. Draft letters from evidence snippets — one specific fact each.
Wednesday. Calls and follow-ups; log outcomes against stable IDs.
Thursday. Review keyword-missed fits — the names no rival letter reached.
Friday. Feed learnings back; a custom ICP re-run is included when your thesis sharpens.
What you receive

Inside the deliverable

A Proof project from €4,900 screens one niche end-to-end. The full universe with deep shortlist starts at €9,900; annual monitoring at €18,000 per thesis.

Questions searchers ask

Straight answers, before you commit a euro

My niche is unusual. Can you screen a thesis that doesn't match a standard industry category?
Yes — that is the normal case, not the exception. The 700+ maintained categories are a starting cut, not a straitjacket. Your written thesis drives the LLM analysis, so "fluid-handling distributors with in-house repair, US Midwest" is a perfectly screenable definition. If the thesis changes mid-search, a custom ICP re-run on any subset is included.
How is this different from the database subscription my fund already pays for?
Profile-based databases index companies someone already found and coded. We start from 100M+ classified domains — the entire active web — and read each site against your thesis. In our specimen runs, a fifth or more of confirmed fits lacked the category's obvious homepage keywords, which means code-and-keyword filters could not have returned them. The two tools can coexist; they do different jobs.
Do you tell me which owners are open to a conversation?
No, and we would advise skepticism toward anyone who says they can. Websites do not reveal intent, and we refuse to infer personal circumstances. What we do document is website-visible context: founder-associated, long-established, independently positioned businesses with an identifiable decision-maker and limited visible leadership bench. Whether a conversation goes anywhere is your craft, not our claim.
What does a Proof project cover for €4,900?
One niche, screened end-to-end with the full pipeline: category cut, triage to live operating companies, deep extraction on the shortlist, scores, verbatim evidence and documented exclusions. It exists so you can judge the output quality on your own thesis before committing to the full universe (from €9,900) or annual monitoring (from €18,000 per thesis). See pricing for details.
How fresh is the data by the time I'm doing outreach?
Each engagement runs against the live web at screening time, not a stored snapshot — the evidence quotes what the site said when we read it, with the URL so you can re-verify. Websites do lag reality in both directions, which is exactly why every claim in the deliverable is sourced rather than asserted.
Will my list be shown to other searchers in my space?
No. The screen runs against your thesis and the deliverable belongs to your engagement. We are not a subscription product where every customer queries the same index — which is also why the same niche can yield different lists for two funds with genuinely different theses. Your edge is the thesis; we keep it that way.

Put a real denominator under your search

Send us the thesis you're searching on. We'll scope the niche, quote the timeline, and show you a specimen of exactly what lands in your inbox.

We publish what we refuse to claim — no intent flags, no financial guesses, no owner profiling. Read our standards.