Pennsylvania Registered Businesses - Officers & Signatories

Pennsylvania publishes its registered-business file as open data - every entity registered with the Department of State, together with the officers and signatories named on each registration. This actor turns that file into a charged-per-record search, filter and aggregate tool: find a business or a person, filter by role or county, or aggregate the register.

Built for: sales and B2B lead-gen (who runs a company), KYC and diligence (who is behind an entity), and anyone who wants the people on a PA registration without paging a portal one name at a time.

What it covers

4,110,251 officer rows across 2,360,829 registered entities. Read the grain before quoting a number: one row is one officer / signatory of a business, not one business - the 4.1M rows average ~1.74 per registration (one filing runs to 160 officers). The value is the person layer.

Each row carries:

• the role (party_type) - President (801,111), Governor (770,661), Organizer (404,232), Treasurer (376,285), Secretary (225,015), Vice President (199,718), General Partner, Incorporator, Member (42,221), Owner (17,642), ...
• the registration type - Domestic Limited Liability Company (1,633,573, the source's exact string - try that, not LLC), Domestic Business Corporation (1,479,469), Domestic Nonprofit Corporation, Foreign Business Corporation (361,273), ...
• the entity's address, city, state and county (Philadelphia 575,656 / Dauphin / Allegheny / Montgomery / ...) and the creation date
• the person's first / middle / last name and the filing number that ties the officers of one entity together

The fine print that matters

Two quirks are handled for you. Role casing is inconsistent in the source - Member / MEMBER / member, Owner / OWNER / owner, PARTNER / Partner - so the role filter folds case (a bare equality match would silently miss two-thirds of some roles). And creationdate carries the sentinel 1753-01-01 on some rows (a .NET zero-date); years before 1900 are blanked on output so a fake 1753 never surfaces, while the genuine - often very old - formation dates are kept.

Worth stating plainly: party_type is blank on 969,859 rows (~24% of the file). That is a real gap in the source, kept as blank rather than dropped or invented.

Typical questions

• "Everyone registered as an officer of a given company."
• "Every entity a person is tied to, by name."
• "All Presidents / Governors / Treasurers in Philadelphia County."
• "Newly registered Domestic Limited Liability Company entities since a date."
• "Aggregate the register by registration type, county or state."

Inputs

Input	What it does
mode	rows (default) / aggregate
businessName / filingNumber	find the entity
officerName / partyType	find the person and their role
registrationType	entity type
county / city / state / zip	where
createdFrom/To	creation-date range
groupBy	aggregate over registration type / county / state
maxResults	cap records (default 50)

Default run = the 50 most recent registrations - fast for the daily auto-test. For a targeted query add a filter; for a broad view use aggregate.

Example inputs

Everyone named on one registration - filingNumber ties the officers of one filing together; a filing runs to as many officers as the entity named.

{ "filingNumber": "0015854682" }

Every entity one person is tied to - officerName matches a first or last name, and partyType narrows it to a role.

{ "officerName": "Vaughn", "partyType": "Organizer", "maxResults": 25 }

New entities of one type in one county - registrationType takes the source's exact string ("Domestic Limited Liability Company", not "LLC").

{
  "registrationType": "Domestic Limited Liability Company",
  "county": "Philadelphia",
  "createdFrom": "2026-01-01",
  "maxResults": 25
}

Where the register concentrates - one count per registration type.

{ "mode": "aggregate", "groupBy": "registrationType" }

Low cost

From $0.0001 per record, down to $0.00006 at Gold - billed only for the rows you use, at the low end of the store. Cost scales with what you pull, not with the size of the register, and each record is metered individually.

What a thin scraper misses is the grain and the casing. This is not a business list - it is the officer layer of one, and quoting "4.1 million businesses" from it would be off by nearly 2; a filing number ties a company's officers back together. The role column is inconsistently cased (MEMBER / member / Member are one role), so a naive filter silently misses two-thirds of some roles, and the creation date carries a 1753 sentinel that sorts to the bottom of any date view. Normalizing the officer-vs-business grain, the role casing and the zero-date into a schema where a businessName / partyType / county query returns exactly the people you mean is the actual product. Every pull is integrity-checked against the register's known shape, so a degraded source fails loudly instead of returning bad rows.

Example output

One officer row - filingNumber=0015854682 returns one record per officer named on that registration:

{
  "platform": "pa-registered-businesses",
  "source": "pa-dos-registered-businesses",
  "mode": "rows",
  "groupKey": "",
  "groupCount": "",
  "groupBy": "",
  "businessName": "Overrated Property Co.",
  "filingNumber": "0015854682",
  "registrationType": "Domestic Limited Liability Company",
  "creationDate": "2026-09-02",
  "partyType": "Organizer",
  "lastName": "Vaughn",
  "middleName": "",
  "firstName": "Derrick",
  "address1": "1012 Pembroke Ave",
  "address2": "",
  "city": "Lansdowne",
  "state": "PA",
  "zip": "19050-2723",
  "county": "Delaware",
  "countyCode": "23",
  "latitudeLongitude": "{'type': 'Point', 'coordinates': [-75.25687, 39.94372]}"
}

mode=aggregate, groupBy=registrationType - one row per group:

Domestic Limited Liability Company   1,633,573
Domestic Business Corporation        1,479,469
Foreign Business Corporation           361,273

Source

• Pennsylvania: Registered Businesses Current by County - the Department of State's registered-business file with officers and signatories. Public open data. Records are the state's own published fields; not an endorsement of any business or person.