Generic News APIs vs Business News APIs: Key Differences Explained

The problem with “good enough” news data

With so many undifferentiated news providers, news has become a commodity. And, accessing news via APIs is easy. However, the real challenge is turning raw, high-volume news into something that can actually be used for decision-making and intelligence workflows. Most News APIs optimize for providing the maximum volume of articles as fast as possible, with faster data ingestion and distribution. 

They provide thousands of articles per day, pulled from tens of thousands of sources. But when you try to use these articles, you’ll come across multiple challenges. For example:

• Duplicate or almost similar stories
• Irrelevant articles that incorrectly match keywords 
• Generic topic tags that don’t map to a consistent business taxonomy
• Non-English content that’s unusable without translation and additional processing

And to use the, you’ll have to build multiple processing layers on top:

• Custom filters
• Deduplication logic
• Translation pipelines
• Entity recognition and disambiguation
• Topic classification
• Summarization

This is the gap that Business News APIs from Contify are designed to address.

Users don’t need more news; they need less noise.

It’s a good idea that’s easy to say, but extremely hard to implement at scale with technology.

Over the years, through multiple iterations, Contify has developed a set of unique capabilities to address the problems. The following sections explain the differentiators behind Contify’s Business News APIs, which deliver not just news data, but analysis-ready business intelligence.

#1: Business-first sourcing, not generic crawling

Generic News APIs focus on “number of sources” as a vanity metric. Contify looks at which sources matter. Yes, the platform pulls from over a million verified sources. But more importantly, these include the original sources of information:

• Company websites and press rooms
• Regulatory and government portals
• Job boards and hiring pages
• Industry-specific publications
• Niche and regional outlets

These are important because the most important business signals don’t appear in mainstream news media unless the news impact is so sensational or so significant that the general public would be interested in it and could generate sufficient clicks or pageviews for the news source to generate advertising revenue.

Generic News APIs often miss these because their primary use case is to measure the news’s reach, not its strategic significance. They focus on the mass media’s sentiment and reach, which are well-suited to a B2C consumer brand.   

#2: Noise-free processing, not raw aggregation

Generic News APIs focus on aggregating raw news and treat relevance as a problem that customers will solve. They aggregate everything, deliver stories that match a keyword, and leave it to the customer to decide what matters.

Contify takes the opposite approach. Relevance is the starting point of the entire system design. It is enforced at each step of data processing in Contify. Every story passes through a multi-step processing pipeline that combines:

• Deduplication of stories
• Filter out irrelevant or low-impact stories that match keywords but are irrelevant to business users
• Disambiguate entities so stories are attributed to the correct company, persons, and locations, not their namesake.

This is important because duplicate and irrelevant stories don’t just waste user time. They erode their trust in your system. When intelligence users see alerts with weak signals, they stop paying attention altogether.

Generic News APIs accept noise as inevitable because their systems are designed for coverage rather than relevance. Contify is designed for relevance, which is what intelligence workflows can use.

#3: Deep business taxonomy, not shallow tags

Generic News APIs offer classification, but it’s too shallow to be used in any meaningful intelligence workflow. Commonly included tags are: 

• Broad categories like “Sports,” “Business,” or “Technology”
• Keyword-based topic labels
• Basic sentiment score

These could work for general consumer sentiment or content reach. However, it doesn’t work for intelligence workflows. 

Contify classifies every story using a deep business taxonomy explicitly designed for decision-making.

To illustrate the depth of this taxonomy, consider how location is handled. Most News APIs tag a location only when it is explicitly mentioned in the article. For example, they may tag a story with “France” if the word appears in the text.

In practice, this approach is insufficient. Many stories about France never mention the country by name, especially articles published by French sources that assume a local context.

Contify addresses this by tagging multiple location dimensions. In addition to mentions within the content, we tag the publication’s source location. More importantly, we also tag the location of the primary companies discussed in the article.

This enables teams to answer strategic questions such as: What are French companies doing in response to the new AI regulations?

Contify offers out-of-the-box business taxonomies, which include:

• Business Events: Specific business events such as funding, partnerships, leadership changes, regulatory actions, and more
• Industries and sub-industries
• Themes
• Type of content, Type of Source, etc.
• Sentiment, and Business-relevant keywords

In addition, Contify allows customers to define custom tags and classifications aligned with their internal frameworks. This is important because organizations don’t need generic categories; they need tags and labels that represent their unique markets, risks, opportunities, and triggers. Custom taxonomy reflects how businesses make decisions, not how news publishers organize content.

#4: Built-in key highlights, not raw article text

Generic News APIs deliver the raw text of the news articles. As a result, customers often end up building:

• Internal summarization tools
• Manual workflows to use the article in newsletters, reports, and dashboards
• Additional AI layers just to derive insights

Contify includes AI-generated key highlights with every story, delivered as concise bullet points that surface the most important information. This changes how news is consumed:

• Users can easily scan the article 
• Newsletters and dashboards become usable instead of overwhelming
• Alerts convey key insights

Summarization at scale is hard to do well, especially across multiple articles in different languages. This is a core capability in Contify, not an optional add-on, because intelligence workflows require speed and are easy for users to consume. 

#5: Multilingual intelligence with built-in translation, not language silos

For global market intelligence, multilingual coverage is essential because many strategic developments first appear in local languages.

Generic News APIs often claim multilingual coverage. In practice, this usually means providing access to non-English articles. Without built-in translation, however, this content remains largely unusable for intelligence workflows.

Contify Business News APIs provide automatically translated content from over 115 languages into English while preserving the original text and its context. Each article then passes through Contify’s full content-processing pipeline, including deduplication, AI-generated key highlights, and entity and topic tagging.

This enables:

• True global coverage without the need to build a separate translation infrastructure
• Consistent analysis across regions and markets
• Visibility into emerging markets where English-language coverage is limited

Translation is a foundational component of Contify’s intelligence platform, not an optional feature.

Use Cases for Generic News APIs

Not all use cases need sophisticated business news APIs. A Generic News API is suitable when:

• You need to analyze media coverage for your brands or key executives. 
• Your use case is non-business-specific, such as sports, entertainment, politics, or crime-related news. 
• You have a strong internal data engineering team already building enrichment, classification, and summarization layers.
• Precision and recall are less critical than raw coverage or speed

In these scenarios, a lightweight Generic News API can be a reasonable starting point.

However, you need Business News APIs when your use case requires:

• Consistent business relevance, not just keyword matches
• Structured intelligence for Competitive or Market Intelligence workflows
• Reliable alerts and early signals with minimal noise
• Scalable AI and analytics pipelines that depend on clean, enriched inputs

The table below summarizes the key differences between Generic News APIs and Business News APIs across key dimensions.

Generic News APIs vs Business News APIs: Key Differences

Dimension	Generic News APIs	Business News APIs (like Contify)
Primary Goal	Provide access to large volumes of news articles	Deliver decision-ready business intelligence
Content Focus	Broad news coverage across many categories (business, sports, entertainment, lifestyle, etc.)	Exclusively business-relevant news
Source Types	Mainly media and news publishers	Tier 1 business media + company websites, press rooms, regulators, job boards, niche industry sources
Relevance Filtering	Largely keyword- or category-based	AI-driven relevance filtering with business context
Noise & Duplication	High duplication and irrelevant matches; cleanup left to users	Built-in deduplication and noise filtering
Event Classification	Rare or very high-level	Granular business-event tagging (e.g., funding, partnerships, regulatory action)
Custom Taxonomy Support	Typically not supported	Custom tags and classifications aligned to internal frameworks
Summarization	Raw article text; summarization is user’s responsibility	AI-generated key highlights are included by default
Multilingual Handling	Access to multiple languages, translation handled externally	Built-in multilingual translation with contextual preservation
Delivery Model	Polling-based API access	Polling + real-time webhooks for instant delivery
AI / LLM Readiness	Requires significant preprocessing	Structured, analysis-ready datasets for AI pipelines
Engineering Effort Required	High (filtering, enrichment, translation, summarization)	Low (intelligence delivered out of the box)
Best Fit Use Cases	Media monitoring, general news consumption	Competitive intelligence, market intelligence, risk, analytics, AI

What this really means for buyers

Generic News APIs are built to collect and distribute general news. Business News APIs are built to deliver relevant updates, enriched with structured metadata, at scale. 

If your intelligence workflows, analytics, and AI systems depend on external signals, this distinction becomes critical. 

The easiest way to understand the difference is to experience it. A free trial of Contify’s Business News APIs lets you see firsthand how noise-free, analysis-ready business intelligence changes what you can build and how quickly you can act.