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News & article data

News & article data, delivered to spec

Production-grade article data: composable, not packaged. Build it yourself on Zyte API, or have it delivered by Zyte Data. Same foundation, your choice of who runs the pipeline.

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The basics

What is news & article data?

News and article data is the structured record of a published piece: its headline, byline, publish date, full body text, images, and topical/entity metadata. It's collected from publisher sites and news aggregators, then cleaned of boilerplate (ads, related-article rails, comment sections, subscription prompts) and normalized into a consistent schema. Because publishers render the same story differently, and often paywall or dynamically inject parts of it, the value is in reliable, clean extraction at the article level, not the raw page.
Who uses it

Use cases across industries

The same data type, put to work differently. Ordered by how directly it applies.

Media & publishers

Aggregate full-text articles and metadata from thousands of sources to power discovery, curation, and syndication products.
Deduplicated across 10,000+ sources

Brand & PR monitoring

Track mentions, sentiment, and share-of-voice across news outlets as they publish, not a day later.
Mentions surfaced within minutes of publish

Investment & market research

Feed earnings coverage, sector news, and executive-mention signals into research and trading workflows.
Structured feed, no manual clipping

Competitive intelligence

Monitor competitor coverage, product launches, and executive commentary across trade and mainstream press.
Coverage mapped by outlet and beat

AI / ML teams

Build clean, deduplicated article corpora for NLP training, summarization, and topic models.
Body-text accuracy benchmarked vs. 5 extractors

Compliance & risk teams

Monitor adverse media and regulatory coverage for KYC/AML and reputational risk screening.
Entity-linked adverse media alerts
Try Zyte APITalk to our Data Experts
The hard part

Why news & article data is hard at scale

The problem is rarely a single article. It's correctly separating story from clutter across thousands of publishers whose templates change without notice.

Boilerplate hides the story

Related-article rails, comment threads, share buttons, and subscription prompts sit in the same HTML block as the article body. Zyte's extraction model is trained to isolate body text from surrounding noise, article by article, not with brittle per-site rules.

Paywalls and lazy-loaded content

Many publishers render the full body only after a scroll event, a login check, or a metered-paywall script fires. Zyte renders pages the way a browser does, so gated and dynamically injected content is captured — within the bounds of each publisher's terms and your license.

The same story, published forty times

Wire stories and syndicated content appear near-identically across outlets within minutes of each other. Zyte deduplicates at the story level so your feed reflects distinct coverage, not forty copies of one AP piece.

Every publisher, a different template

Thousands of source templates means thousands of ways to mis-extract a byline or a date. Zyte validates extraction quality per source, not just per field, and flags drift when a redesign breaks a previously reliable source.
The cost of getting it wrong

What bad news data quietly costs the business

Bad article data doesn't announce itself. It shows up later, in a sentiment score, a research note, or a trained model that was already wrong.
Signal Lag
Mentions detected hours late are mentions acted on too late; a monitoring feed built on stale crawls misses the news cycle it exists to catch.
Duplicate Inflation
Uncounted syndication can make a single wire story look like broad organic coverage, skewing share-of-voice and sentiment metrics.
Model Degradation
An NLP model trained on boilerplate-contaminated text degrades quietly; ad copy and related-link text leak into what the model treats as "the article."
Regulatory Exposure
Collecting and republishing content without regard to publisher terms, copyright, or personal-data rules carries real legal risk, including GDPR exposure up to €20M.
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See the Schema

The request you send and the data that comes back. Pick the standard schema or a custom one mapped to your model, and read the response as a table or JSON.

Zyte API
REQUEST
POST https://api.zyte.com/v1/extract
{
  "url": "https://example-news.com/story/2026-market-outlook",
  "article": true
}
RESPONSE
Standard article Schema
Field
Type
Example
url
string
https://example-news.com/story/2026-market-outlook[https://example-news.com/story/2026-market-outlook]
headline
string
"Markets steady after rate decision"
articleBody
string
"Full cleaned article text..."
articleBodyHtml
string
"<p>Cleaned HTML...</p>"
datePublished
string
2026-06-30T09:12:00Z
dateModified
string
2026-06-30T11:40:00Z
author
array
[{"name": "Jane Doe"}]
publisher
object
{"name": "Example News"}
mainImage
object
{"url": "https://..."}
images
array
[{"url": "https://..."}]
inLanguage
string
en
isAccessibleForFree
boolean
false
entities
array
[{"name": "Federal Reserve", "type": "Organization"}]
category
array
["Markets", "Economy"]
Reviews

What our users say

I have been working with Zyte's team for the last few months, and their team is fantastic. I appreciate their development speed and quality, and they run a very robust platform, producing very satisfactory results. I love the ease of the initial setup with Zyte, as they took care of all the development, and we only needed to communicate what data we needed and set up the necessary processes on our end.

DP
David P.

The best thing about Zyte is their flexibility. There was a certain website that we needed to crawl. They were able to adapt their code to increase its capabilties. Zyte has a good amount of features and different offerings. Customer support is very good, technical and business. Easy to use and integrate in our code base.

TL
Thierry L.

I find Zyte really easy to use, and it was very easy and pretty self explanatory to set up. We were able to integrate the information we pull into our website to directly compare pricing with other leading companies. Zyte allows us to easily set up the site scrapes exactly how we need it, and it does exactly what we need it to do, always providing a way to make that happen.

BB
Brandon B.

I like Zyte's pricing model which offers a pay-as-you-go level. You only pay when Zyte successfully retrieves the HTML page, and if Zyte has an error, you don't pay. Their support is responsive and their platform is accessible via API. Additionally, the integration with the Python library was simpler.

FP
Florian P.

I love Zyte's after-sales service. Additionally, the setup process was straightforward because I had the support of the technical team and the Customer Success Manager at all times. I greatly appreciate that Zyte delivers value, which is very valuable to us, especially considering the complex programming work and the continuous changes on competitors' web pages.

JS
Jose S. (daas)

Zyte help build our web scrapers and ensure we get structured data regularly. They are the most personable supplier I've worked with, and it's great to meet the people behind it regularly. Communication is straightforward. If there's an issue, I can sit with them and find a solution collaboratively.

AM
A. M.

I love the simplicity of integrating Zyte into existing Python code. The API is very convenient because it automatically handles retries in case of failure and allows for parallelizing requests. The initial installation of Zyte was very easy.

YM
Yann M.

We used Zyte because it's a reliable way to scrape large amounts of data without risking being blocked by websites' security systems. I really appreciate its 'do once and forget about it' approach; we set everything up once, and it continued to work for years without a hitch. The reliability is impressive - it always works, and for a scraping tool, that's very important.

AN
Alexandr N.

Get a news data feed scoped to your sources

Talk to a data specialist about coverage and schema, or request sample data for the outlets you care about.

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Frequently asked questions

How fresh can news & article data be?

New articles are typically detected and delivered within minutes to hours of publication, depending on source polling frequency. Real-time delivery is available where the use case needs it.

How do you handle paywalls and gated content?

Coverage is scoped per source and per license — Zyte captures what a compliant, authorized method allows for each publisher, and this is agreed upfront rather than assumed.

How do you handle wire syndication and duplicate stories?

Articles are deduplicated at the story level using content-similarity matching, so near-identical syndicated copies don't inflate your feed or your metrics.

What fields and formats do you support?

Standard fields include headline, byline, publish/modified dates, full body text and HTML, images, language, paywall status, and extracted entities/categories. Custom schemas are available on request; delivery via JSON, API, or batch file.

How do you approach compliance for news data?

Collection is scoped to each publisher's terms and applicable law, with sensitive personal data excluded by default unless specifically required and authorized.

How long does setup take?

Most feeds go from scoping call to first delivery within one to two weeks, depending on source count and schema complexity.

Can I see a sample before committing?

Yes — request sample data for specific outlets during your first call with our data specialists.

Can I see a sample before committing?

Yes. Talk to a data specialist to request sample data from the sources you care about before agreeing to a contract.

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