Real estate data scraping — listings in, dataset out
Real estate data scraping collects listings, prices and agent details from property sites into structured rows. Quantic AI runs it end to end: it finds the portals and agency sites for your market, maps their listing sections and scrapes the fields you name — beds, price, size, contact — into CSV or JSON.
$1 free every month · No card required · Blocked pages are never billed
# "2-bed apartments for sale in Valencia under €250k" search("apartamentos 2 habitaciones valencia", es) → portals + 9 agency sites · $0.0005 map(agency sites) · find /venta, /listings → listing sections located · $0.0045 scrape(listing pages, extract: price, m², rooms) → rows: { "price": "€238,000", "m2": 87, "rooms": 2, "agency": "…" }
How it works
From a market question to a listings table
1 · Search the market, in its language
Queries run in the market's own terms — "apartamentos en venta valencia", "wohnung kaufen leipzig" — across three engines via the SERP API, surfacing local portals and the agency sites that never syndicate to them.
2 · Map the listing sections
Each site's map call reveals where the inventory lives — /venta, /listings, /immobili — the same way our real pipeline run found a roaster's 28-page /producers section in one call. No per-site template to build.
3 · Extract listing fields
Listing pages go through the scraping API with your schema: price, size, rooms, floor, energy class, agency contact. JS-heavy portals escalate to a rendering browser automatically.
4 · Rows you can model
Deduplicated rows with source URL and timestamp — €/m² by district is one pivot away. Rerun weekly and diff for price cuts and time-on-market signals.
A real estate data API under the hood
Everything the prompt does is also callable directly: search, map, scrape and batch as REST endpoints or MCP tools — the same AI web scraping service pipeline, exposed for your code. Proptech teams can wire listings collection into their stack without renting a per-portal feed.
Rendering is built in for the JavaScript-heavy portals, geo-routing puts the request in the listing's country, and every response carries its cost — so the unit economics of your data product are visible from call one.
A property listings dataset, market by market
Fortress portals — the Zillow-class giants — defend their inventory hard, and nobody can honestly promise them at 100%. What pay-per-success changes is the risk: a blocked page bills nothing, so probing the hard targets costs you attempts, not money.
The underrated inventory is everywhere else: local portals, agency chains, single-office sites with twenty exclusive listings each. Search-driven discovery reaches that long tail — the part of the market per-site scraper templates never cover.
Prompt pipeline vs a per-site scraper template
| Quantic AI dataset | Typical scraper template | |
|---|---|---|
| Coverage | any site search can find | one site per template |
| Setup | a prompt | build & maintain selectors per portal |
| Site changes | extraction adapts per page | template breaks silently |
| Geo | residential exit in the market | your IP, often blocked |
| Failed pages | never billed | your time either way |
What does a listings scan cost?
With Quantic AI (planned): 300 listings × $0.03 ≈ $9 plus metered pipeline — listing fields are standard columns, no premiums. DIY on the raw APIs: $0.07–0.31 in unit prices, with the scraper, retries and upkeep on you.
Is it legal to scrape data from Zillow?
Zillow's terms of service prohibit automated collection, and it enforces that technically — so we don't treat it as a target. Publicly visible listing facts in general (asking price, size, rooms, location) are usually lawful to collect, but the portal's own terms still bind you and some jurisdictions protect databases as such. The durable approach is to collect from agency sites and portals whose terms allow it, keep provenance per row, and take advice for your market.
Is it legal to scrape real estate listings?
Publicly visible listing facts — asking price, size, rooms, location — are generally lawful to collect in most jurisdictions. Portal terms of service vary and some jurisdictions protect databases as such; agent names are personal data under GDPR-style laws. Collect public pages, keep provenance, and get advice for your market.
How to scrape real estate agent data?
Agency sites are the honest source: a search pass finds agencies in the area, map discovers their /team and /agents pages, and extraction reads the public office contacts published there. Note that named agents are personal data under GDPR-style laws — prefer office-level contacts, honor opt-outs, and keep the source URL and timestamp on every row so you can prove where a field came from.
What fields can I extract from a listing?
Whatever the page shows: price, address or area, size, rooms, floor, energy class, listing date, description, photos count, agency name and public contact details. You name the columns in the prompt and structured extraction returns exactly those, with the source URL per row.
Can it access MLS data?
No. MLS feeds are licensed member systems, not public pages, and this pipeline reads the public web only. What it can do is collect the public marketing side of the same market — portal listings and agency websites — which for most analyses is the observable layer that matters.
Does it work on the big portals like Zillow?
Large portals are the most defended targets on the web and actively fight collection. Requests route through residential exits and escalate to a rendering browser, but success is never guaranteed — and that's priced in: a blocked page costs nothing. Agency sites and mid-size portals are far softer ground.
How much does a listings dataset cost?
With Quantic AI, planned pricing: $0.03 per delivered listing — a 300-listing scan lands around $9 plus metered pipeline usage, and listing columns are standard fields with no premiums. Developers can run the same scan on the raw APIs for $0.08–0.31 in unit prices, scraper and upkeep on their side.
How fresh are the listings?
As fresh as the moment you run it — collection happens at request time and every row is timestamped. Rerun the prompt weekly and you get time-on-market and price-cut signals by diffing runs, without subscribing to anyone's index.
Your market's inventory, in rows
Start with $1 free every month — or join the Quantic AI waitlist for the full prompt-to-dataset service.
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