Listings, rents, comps, agent profiles, and location attributes across US regions — structured datasets for PropTech, investors, and market researchers.
PropTech companies, REITs, real estate marketplaces, and rental investors all need the same thing: clean, comparable property-level data across multiple US listing sources. We extract from public listing platforms and deliver structured comps you can actually model on.
Address, beds/baths, sqft, lot size, year built, list price, days on market, listing status.
Price changes, sold price (where surfaced), days on market trends, price-cut signals.
Rent asks, lease terms, amenities, pet policy, unit availability for multifamily and SFR rentals.
Closest comps where surfaced, neighborhood demographics joins, school ratings.
Agent name, brokerage, contact, listing history, market activity.
Lat/long, parcel matching where possible, ZIP/metro/state rollups.
| Source | Listing ID | Address | City/State | Beds/Baths | Sqft | Price | Status | Captured (UTC) |
|---|---|---|---|---|---|---|---|---|
| Source A | LST-4400-12 | 402 Oak Ave | Austin, TX | 3/2 | 1,820 | $489,000 | Active | 2026-05-19 10:30 |
| Source B | MLS-99-3104 | 88 Mission St #4 | San Francisco, CA | 2/2 | 1,140 | $1,295,000 | Pending | 2026-05-19 10:30 |
| Rental A | RNT-119-880 | 1240 Main St | Phoenix, AZ | 1/1 | 660 | $1,650/mo | Available | 2026-05-19 10:30 |
Sources we typically cover: Major US listing platforms · Public county records (selectively) · Rental marketplaces · Brokerage sites
Aggregate listings, normalize across sources, surface in your app.
Build rent comps and acquisition pipelines by metro.
Augment underwriting models with property and neighborhood attributes.
Track inventory trends, price cuts, and market velocity by region.
30-min call to confirm sources, fields, frequency, and output schema.
Sample dataset delivered for your team to validate coverage and quality.
Scheduled jobs, monitoring, retries, reporting — backed by uptime SLA.
MLS access is licensed and rules vary by region — we work with publicly listed marketplace data and public records, not direct MLS feeds.
Down to lat/long, ZIP, and parcel ID where surfaced. Aggregations to neighborhood, city, metro, and state are part of standard delivery.
Yes — we capture price history per listing for the period we monitor.
Address normalization + listing-attribute matching produces a master entity with source-level details retained.