NYC Landlord Registry Lead List — HPD Portfolio Contacts
Pricing
from $8.25 / 1,000 results
NYC Landlord Registry Lead List — HPD Portfolio Contacts
Bulk NYC landlord & managing-agent contact lead lists from HPD building registrations. Killer filter: portfolio size — target owners of 5-50 Bronx buildings. Rolls up buildings per contact with business address, boroughs, ZIPs & samples. For prop-mgmt, insurance, lender & proptech sales.
Pricing
from $8.25 / 1,000 results
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Kyle Maloney
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9 hours ago
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Build bulk landlord and managing-agent contact lead lists from New York City's legally mandated HPD (Housing Preservation & Development) registration data — with the one filter no flat data dump gives you: portfolio size per landlord. Ask for "owners of 5–50 Bronx buildings" and get one clean lead record per unique contact, with their filed business address and a rollup of every building they're registered on.
Every residential building with 3+ units (and many 1–2 unit non-owner-occupied buildings) in NYC must register annually with HPD and name an owner, head officer, and managing agent. That makes this the most complete, legally mandated landlord contact registry in the United States — refreshed continuously on NYC Open Data.
Who it's for
- Property-management companies prospecting owners in a target borough / portfolio band
- Insurance brokers (landlord policies, umbrella, builders risk) building call lists
- Lenders & mortgage brokers targeting multi-building owners for refi outreach
- Contractors, roofers, boiler/elevator service companies selling to building operators
- Proptech sales teams who need decision-maker (HeadOfficer / Agent) leads, not LLC shells
- Real-estate investors & brokers mapping who actually controls a neighborhood
What it does (the transform)
- Pulls HPD Multiple Dwelling Registrations for your borough/ZIP (dataset
tesw-yqqr). - Filters to current registrations only — registration end date on/after the
dataset's own latest filing date (anchored to the data, not the wall clock; NYC
registrations run in annual cycles ending September 1). Set
includeExpired: trueto keep lapsed registrations too. - Pulls the matching HPD Registration Contacts (dataset
feu5-w2e2) in batched SoQLIN (...)queries, joined onregistrationid. - Groups by normalized contact identity — corporation name (case/punctuation
normalized) or person first+last name, plus filed business address — so the same
management company across 40 buildings becomes ONE lead with
buildings_count: 40. - Applies your lead filters: contact types, min/max portfolio size, entities only.
- Outputs leads sorted by portfolio size (largest first), capped at
maxResults.
Example input
{"borough": "BRONX","contactTypes": ["HeadOfficer", "Agent"],"minPortfolioBuildings": 5,"maxPortfolioBuildings": 50,"entityOnly": false,"maxResults": 500}
Output fields
| Field | Description |
|---|---|
contact_name | Person name (falls back to corporation for pure entity records) |
corporation | Corporation/LLC name as filed, or null for individuals |
contact_type | Most frequent role: HeadOfficer, Agent, CorporateOwner, IndividualOwner, Officer, SiteManager... |
contact_types | All roles this identity appears under |
business_address / business_city / business_state / business_zip | Filed business address |
buildings_count | Portfolio size — distinct registered buildings linked to this contact in the scanned area |
boroughs / zips | Where the portfolio's buildings are |
sample_buildings | Up to 5 buildings as "housenumber streetname, borough" |
registration_ids_count | Distinct HPD registrations this contact appears on |
is_entity | true = corporation/LLC, false = individual person |
source_url | NYC Open Data source dataset |
Use as an MCP tool
This actor is callable by AI agents (Claude, Cursor, custom agents) via
mcp.apify.com — the described input schema and field-level output docs make it a
clean chainable tool for "find me NYC landlord leads" workflows.
FAQ
How do I get a list of NYC landlords by portfolio size?
Set minPortfolioBuildings / maxPortfolioBuildings (e.g. 5–50) and a borough.
Portfolio size is computed within the scanned area, so a Bronx run counts Bronx buildings.
Is this data legal to use for outreach? The addresses are business addresses filed under NYC Housing Maintenance Code §27-2097, published as public open data by the City of New York precisely so the public can identify who is responsible for a building. No phone numbers or emails are in the source; this actor republishes only what the city publishes.
Which contact type should I target?
HeadOfficer (the decision-maker behind the owning entity) and Agent (the managing
agent who buys services day-to-day) are the highest-value roles. CorporateOwner
rows give you the owning LLC itself.
Does it include expired registrations?
No — by default only current-cycle registrations (end date on/after the dataset's
latest filing date). Set includeExpired: true to include lapsed ones, e.g. to
prospect owners who fell out of compliance.
Can I run it city-wide?
Yes — leave borough empty. Expect a much longer run (~165k current registrations
across all five boroughs); borough-by-borough runs are faster and cheaper.
What about new-landlord alerts? A delta mode (only contacts on registrations filed since your last run) is planned for v1.1.
Pricing
Pay-per-result: you're charged only for the lead records actually pushed to the dataset. Runs that match nothing cost only the minimal actor start.
Data sources
Both are keyless, public NYC Open Data (Socrata) endpoints maintained by the NYC Department of Housing Preservation & Development.
Related actors — the NYC investor shelf
| Actor | What it adds |
|---|---|
| NYC Distressed Property Leads | Which of those buildings are actually under pressure (violations, liens, evictions) |
| NYC ACRIS Deed Transfer Intel | Whether the owner has been buying or selling, with price and cash/LLC flags |
| Parcel Owner Lookup | Address → owner of record for one-off checks |
Typical play: build a portfolio-banded contact list here → screen those BBLs for distress → time the outreach against recent ACRIS activity.