Extract Beta
Turn web pages into structured data.
Turn supported websites into the fields you need.
Extract turns supported websites, protected or not, into typed JSON, without building brittle parsers.
Pull only the fields that matter, even from pages that block ordinary tools: prices, contacts, terms, listings. Ready for your CRM, your dashboard, or your inbox.
What you'd write without Extract
What your team normally pays for
- Selector code CSS or XPath for every field, written per page type
- Parser logic Normalize raw text into typed values: price, date, units
- Failure detection Notice when a selector stops matching before bad data ships
- Schema rewrites Update selectors every time the site redesigns its DOM
- Multi-site adapters A separate extractor per domain, plus routing logic to pick the right one
- Output validation Assert field types and shapes before data reaches your pipeline
The thesis
Get structured data without writing a parser.
The page tells you what matters.
Extract reads the DOM. Emits typed fields. No selectors, no parser code, no maintenance when the page changes.
Show us the website. We figure out which fields are on the page. No setup, no code, no maintenance when the page changes.
await extract({ url: "walmart.com/ip/123" })
One call. Every field. No selectors to write.
One request. Every field. No setup on your side.
- title Apple iPhone 15 128GB
- price 799.00
- currency USD
- rating 4.7
- reviews 2,143
- in_stock true
- images [ 6 ]
- brand Apple
- sku MTM9-128-BLK
- breadcrumb Electronics › Phones
- seller Walmart.com
- description Lightweight titanium, 6.1″ Super Retina XDR display…
The mechanic
Discovered, not parsed.
Found, not built.
Extract scans the DOM, finds fields by shape, emits typed JSON. Watch it land below.
We read the page like a person would. The right fields come out the other side. Watch them land below.
-
01
"title": "Apple iPhone 15 128GB" -
02
"price": 799.00 -
03
"rating": 4.7 -
04
"in_stock": true -
05
"images": [ 6 ] -
06
"cta_label": "Add to cart"
Coverage
One extractor. Every supported site.
Built in. For the sites that matter.
Zenrows builds and maintains a tailored extractor for each supported site. No schema to define, no selectors to write, no parser to fix when the page changes.
We already know these sites. Point Extract at one and get clean fields back, no setup on your side.
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walmart.com E-commerce + title + price
Product pages: title, price, rating, and stock, detected automatically.
Product listings, priced and in stock, pulled with zero setup.
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booking.com Travel + price + availability
Listing pages: price, dates, and rating, no selectors needed.
Stay listings, ready to compare.
-
linkedin.com Professional + name + title
Profile pages: name, title, and company, structured on arrival.
Profile details, structured the moment you ask.
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zillow.com Real estate · +34 more + price + address
Listing pages: price, address, and square footage. 38 sites supported and growing.
Property listings, ready for your dashboard. 38 sites supported and growing.
Need a site that's not on the list? Drop extract=auto and use css_extractor instead, your own CSS selectors, works on any page. See css_extractor
Need a site we don't cover yet? Point your developer at css_extractor instead, it works on any page, with a bit more setup. Learn more
The handoff
Stop writing parsers.
Stop guessing the data.
Free, always. 5,000 credits every month. No selectors to write.
A free plan: 5,000 credits every month. No code to write, no maintenance to fund.
GET
api.zenrows.com/v1/?extract=auto