Real Estate

Aggregate Listings
Across Every Platform

Property portals render listings in the browser and put challenge pages in front of automated clients. FineData reads them the way a browser does, so you can build a property database from public listings.

The Real Estate Data Problem

Property data is scattered across dozens of listing platforms, each with its own anti-scraping defenses. Building a unified view of the market means overcoming these barriers at scale.

Challenge Pages Mid-Run

Large portals present a challenge page after a handful of automated requests, so a run that started fine stalls part-way through.

Plain HTTP Clients Get Interstitials

Large portals are tuned for real browsers. A bare HTTP client without a browser TLS profile and a JavaScript engine often never reaches the listing itself.

Interactive Map-Based UIs

Many platforms load listings dynamically as users pan and zoom maps. This data only exists in the JavaScript runtime, not in the initial HTML.

Fragmented Data Sources

Property data is spread across multiple regional and national platforms. Each has different page structures and different anti-bot measures.

How FineData Solves It

Full-browser rendering, residential exit IPs and inline challenge handling in one API call — without running browser automation infrastructure yourself.

Challenges Handled Inline

When a challenge appears mid-request, it is handled inside the same API call — no second service to integrate. A request that does not come back with the page is not billed.

Browser-Grade Requests

Requests run in a real browser with a matching TLS profile and can exit through residential IPs in the market you are researching.

Dynamic Content Capture

JS rendering captures listings loaded by JavaScript frameworks. Map-based interfaces, lazy-loaded images, and expandable property details are all captured.

Read Listings In One Call

Turn on JS rendering and challenge handling in the request. FineData works through the interstitials and returns the listing content itself.

Challenges handled inline -- no separate service, and failures are not billed

Residential proxies match the geographic market you're researching

Full HTML output ready for parsing with your preferred library

listing_scraper.py
import requests

# Read public property listings from a JS-rendered portal
response = requests.post(
    "https://api.finedata.ai/api/v1/scrape",
    headers={"x-api-key": "fd_your_key"},
    json={
        "url": "https://listings.example.com/homes/san-francisco?min_price=500000",
        "use_js_render": True,
        "solve_captcha": True,
        "use_residential": True,
        "js_wait_for": "selector:.listing-card",
        "tls_profile": "chrome124",
    }
)

data = response.json()
html = data["content"]

# Parse property listings
from bs4 import BeautifulSoup
soup = BeautifulSoup(html, "html.parser")

for listing in soup.select(".listing-card"):
    price = listing.select_one(".price").text
    address = listing.select_one(".address").text
    beds = listing.select_one(".beds").text
    print(f"{address}: {price} | {beds}")

The solve_captcha flag lets the request work through a challenge page before returning the content, and it is only charged when a challenge is actually encountered.

Why Real Estate Teams Choose FineData

Fewer Manual Stops

Challenge pages are handled inside the request, so your pipeline does not queue up work waiting on a human.

Multi-Platform Coverage

Scrape any real estate website with one unified API. No need for site-specific scrapers or browser extensions.

Price Trend Tracking

Schedule regular scrapes to build historical price data. Identify market trends and investment opportunities over time.

Local Market Data

Residential proxies in target regions ensure you see the same listings and prices as local buyers.

Frequently Asked Questions

Which real estate platforms can FineData scrape?
FineData is a general-purpose API rather than a set of per-site integrations: you provide the URL, so there is no hard-coded list of supported portals. What it will not do is sign in to an account, pass a paywall, or reach a listing that a visitor could not open — see the Acceptable Use Policy.
How does CAPTCHA solving affect request cost?
Challenge handling adds 10 tokens to the request cost. A typical property scrape with JS rendering, challenge handling and residential proxies costs around 19 tokens per request (1 base + 5 JS + 10 CAPTCHA + 3 residential). If no CAPTCHA is encountered on a particular request, the CAPTCHA solving tokens are not charged -- you only pay for features that are actually used.
Can I scrape map-based listing interfaces?
FineData's JS rendering executes all page JavaScript including map initializations. However, for best results with map-based UIs, use the list view or search results page rather than the map view. List views contain structured data that's easier to parse and typically include all the same property information. Use js_wait_for: "selector:.listing-card" to ensure listings are loaded before capturing.
How do I handle pagination across listing pages?
Construct URLs for each page (e.g., adding ?page=2, ?page=3) and submit them as individual requests or as a batch. Use session_id to maintain the same proxy IP across pages, reducing the chance of triggering bot detection during pagination. The batch endpoint processes up to 100 URLs in parallel.

What this is for

Publicly listed property information — asking price, address, features, listing history. FineData does not sign in to accounts, does not pass paywalls, and does not reach content a visitor could not open. Agent names and contact details are personal data: collecting them needs a lawful basis, and that responsibility stays with you. The Acceptable Use Policy sets out both in full.

Start Aggregating Property Data

Get free tokens and start scraping real estate listings today. CAPTCHAs solved automatically. No infrastructure to maintain.