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Longlists

Build a longlist of companies

longlists_find · Reads only · Markdown

Companies that fit a brief (industry, headcount, revenue, distance, ownership) from four registers, each scored out of 100 with its reasons.

$0.02 per company returned

From your agent’s balance. A call that fails costs nothing.

An example

Find makers of food-service machinery in France and Norway with 20 to 200 staff and €5 to 100 million revenue that we could buy.

Your agent callslonglists_find$0.02 per company returned

The example business is Hansen & Voss, a restaurant-equipment wholesaler in Hamburg with 60 staff. The reply is the one the tool really gives.

With these arguments
{
  "industries": [
    "28.93"
  ],
  "countries": [
    "FR",
    "NO"
  ],
  "employees": {
    "min": 20,
    "max": 199
  },
  "revenue_eur": {
    "min": 5000000,
    "max": 100000000
  },
  "limit": 30
}
What comes back
{
  "companies": [
    {
      "id": "fr:946250420",
      "name": "RATIONAL WITTENHEIM SAS",
      "country": "FR",
      "number": "946250420",
      "status": "active",
      "city": "Wittenheim",
      "industry": {
        "scheme": "NACE Rev. 2",
        "code": "28.93",
        "label": "Manufacture of machinery for food, beverage and tobacco processing"
      },
      "founded": "1962-01-01",
      "employees": {
        "min": 100,
        "max": 199
      },
      "revenue": {
        "amount": 86582337,
        "currency": "EUR",
        "year": 2025
      },
      "net_income": {
        "amount": 4958926,
        "currency": "EUR",
        "year": 2025
      },
      "ownership": {
        "signal": "independent",
        "basis": "inferred",
        "evidence": "No company among its leaders in the register; a group can still own it"
      },
      "source": "https://annuaire-entreprises.data.gouv.fr/entreprise/946250420",
      "score": 100,
      "reasons": [
        "Industry 28.93 (Manufacture of machinery for food, beverage and tobacco processing): the same industry as asked",
        "Headcount 100 to 199, inside 20 to 199"
      ]
    },
    {
      "id": "fr:875420192",
      "name": "MAGUIN SAS (K MAGUIN)",
      "country": "FR",
      "number": "875420192",
      "status": "active",
      "city": "Charmes",
      "industry": {
        "scheme": "NACE Rev. 2",
        "code": "28.93",
        "label": "Manufacture of machinery for food, beverage and tobacco processing"
      },
      "founded": "1954-01-01",
      "employees": {
        "min": 100,
        "max": 199
      },
      "revenue": {
        "amount": 41391398,
        "currency": "EUR",
        "year": 2024
      },
      "net_income": {
        "amount": 4012780,
        "currency": "EUR",
        "year": 2024
      },
      "ownership": {
        "signal": "group",
        "basis": "stated",
        "evidence": "Président de SAS: MORET INDUSTRIES PARTICIPATIONS (fr:585781305)"
      },
      "source": "https://annuaire-entreprises.data.gouv.fr/entreprise/875420192",
      "score": 100,
      "reasons": [
        "Industry 28.93 (Manufacture of machinery for food, beverage and tobacco processing): the same industry as asked",
        "Headcount 100 to 199, inside 20 to 199"
      ]
    }
  ],
  "considered": {
    "FR": 25,
    "NO": 7
  },
  "unavailable": [],
  "notes": [
    "Norway's register lists headcount but no revenue in a search: revenue counts as unknown (half marks); companies_financials reads the accounts per company.",
    "France: with a revenue range, only companies that publish their revenue come back."
  ],
  "scoring": "The share of the points the brief asks for: industry 30, headcount 20, revenue 20, distance 15, ownership 15, business model 20. A fact the register doesn't publish earns half its points, and every point has its reason. Where a register's NACE Rev. 2.1 class also holds other industries, the industry earns two thirds; a UK accounts class stands in for headcount, at 15 for a fit."
}

Use it when

To build a target list for an acquisition, or a list of companies like one you know.

What it does

Companies that fit a brief, in any country: from its register where Conecto reads one that lists industries (Conecto's index of its operating companies, or the register live around a point), and from the businesses on the map everywhere else (Overture Maps, and OpenStreetMap daily in Germany). Give the industries as NACE codes and, as the brief needs, headcount and revenue ranges, a point and radius, family-run or part of a group, and the business model in words; each company comes back scored out of 100 with its reasons and its facts, best first. What a source doesn't give earns half marks and says so, and a business from the map has its industry inferred from its listing. Read a register company further with companies_get and companies_financials.

What comes back

companies (id, name, country, number, city, industry, employees, size (the UK's accounts class), revenue, net_income, ownership with its evidence, description where the register has one, website, distance_km and site near a point, score, reasons, source), considered (companies per register), unavailable, notes and scoring. Every reply also carries cost_usd and balance_usd.

Inputs

NameTypeWhat it is
industriesRequiredarray of stringsNACE Rev. 2 codes: a division (28), a group (28.9) or a class (28.93). Norway and newer Finnish filings are on NACE Rev. 2.1, searched under what each code became. 1 to 10 items.
countriesarray of stringsThe countries to search, as ISO codes ("DE", "BR") or names ("Germany", "Brasil"). Any country works: one whose register Conecto reads comes from it, every other from the businesses on the map (Overture Maps, and OpenStreetMap daily in Germany). Left out: the registers Conecto reads. 1 to 30 items.
employeesobjectHeadcount range, e.g. {"min": 20, "max": 199}.
employees.minnumber0 to 10,000,000,000,000.
employees.maxnumber0 to 10,000,000,000,000.
revenue_eurobjectRevenue range in euros (France publishes revenue; elsewhere it counts as unknown).
revenue_eur.minnumber0 to 10,000,000,000,000.
revenue_eur.maxnumber0 to 10,000,000,000,000.
nearobjectCompanies with a site within km of a point: 500 km at most, and 50 in France, whose register measures it.
near.latRequirednumber-90 to 90.
near.lonRequirednumber-180 to 180.
near.kmRequirednumber1 to 500.
near.placestringThe town, matched where a register gives no coordinates. Up to 100 characters.
ownershipstringindependent: no company leads it; group: part of a group. One of: independent,group.
business_modelstringWhat the companies do, in words a register might use, in English or the country's language ("combi ovens for restaurants, storkjøkken"). It ranks within the industries given: Norway by the purpose companies registered, by meaning; elsewhere by the words of their names, map listings and industries, so give the narrowest class. Up to 300 characters.
excludearray of stringsCompany ids to leave out, like the ones already contacted. Up to 500 items.
limitinteger1 to 200. Default: 50.

The call

Over MCP, call longlists_find on https://api.conecto.chat/mcp/longlists. Over REST:

Terminal
curl -X POST https://api.conecto.chat/v1/tools/longlists_find \
  -H "Authorization: Bearer $CONECTO_KEY" \
  -H "Content-Type: application/json" \
  -d '{"industries":["28.93"],"countries":["FR","NO"],"employees":{"min":20,"max":199},"revenue_eur":{"min":5000000,"max":100000000},"limit":30}'

When it refuses

A refused call costs nothing and says what to do next.

CodeWhenWhat to do
invalid_input400An industry code that isn't NACE at the division, group or class level, or a country whose register can't be searched by industry (Germany among them).Give codes like 28 or 28.93; search German companies by name or HRB number with companies_search.
unavailable503None of the registers asked answered.Try again in a minute.

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