News Publishing Platform

Turning incoming news feeds into publishable content requires its own workflow

Content received from news services is rarely ready to be published as-is. Incoming articles need to be placed in the correct category, adapted to the publication language, prepared with headlines and summaries, enriched with SEO metadata, and checked to prevent the same story from being published multiple times. When different news websites have different category structures and editorial preferences, managing these steps manually becomes even more difficult. The platform was developed to automatically process external news feeds and transform them into a controlled publishing flow adapted to the needs of each destination site.

Processing NewsData.io articles through a centralized pipeline

The platform uses NewsData.io as its external news source. Articles received through the API are not sent directly to publication. They first enter a centralized processing workflow. An orchestrator tracks the current stage of each article and routes the necessary tasks through the relevant AI processing steps. Within this pipeline, articles are classified, summarized, rewritten when needed, adapted to the target language, assigned a headline, and enriched with SEO metadata. The content is then mapped to the appropriate category structure of the destination news website.

Adapting each article to the publishing structure, not just rewriting it

Not every news website uses the same category tree, editorial structure or language preferences. The platform processes incoming articles according to the requirements of each destination site. Category mapping can be configured per site, content can be translated when required, and headline and summary fields can be prepared according to the publication format. News detail pages can also include a separate AI-generated summary field. This allows the same external data source to serve multiple publishing projects while respecting the content structure of each individual site.

Detecting repeated stories before publication

News feeds may contain the same or highly similar stories as separate records. The platform checks incoming content for duplicates before allowing it to continue through the publishing flow. This reduces unnecessary repetition and helps prevent the same story from being published more than once.

Balancing automatic publishing with editorial review

The default publishing model is automated. When an article meets the required conditions, it proceeds without editor intervention and is delivered to the appropriate news website. If the system determines that editorial review is required, the article is removed from the automatic publishing flow and routed to an editor instead. This preserves automation at high volume while keeping human review available for exceptional cases.

Managing source attribution according to publishing policy

Source attribution can be configured according to tenant or publication policy. The original source can be displayed when required by the customer, and agency attribution is retained when the article originates from a news agency. This allows different publishers to apply their own source-attribution rules within the same platform.

Using images from the source feed

Article images are taken from the data provided through NewsData.io. This project does not use a separate AI image-generation workflow. The image flow therefore remains part of the same external news-feed pipeline.

Processing and publishing workflow

Area	Responsibility
News source	Receiving content from NewsData.io
Classification	Evaluating article type and context
Summarization	Preparing a short summary and AI summary field
Rewriting	Adapting content to the target publication structure
Language adaptation	Translation when required
Headline generation	Preparing a publication-ready headline
SEO metadata	Generating titles, descriptions and related metadata
Category mapping	Assigning the article to the appropriate category on the destination site
Duplicate control	Preventing repeated or duplicate stories
Editorial review	Routing selected articles to human review
Publishing	Automatically publishing content that meets the required conditions
Images	Using article visuals supplied through the source API

Real-world operating scale

The platform is currently active in production across 5 different news websites. Publishing volume varies depending on each site's category scope and the types of news it follows.

Turn high-volume content feeds into controlled publishing systems.

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Not treating external feed data as publication-ready content

The platform's core approach is to separate external news data from the final published article. Content received from the source API first enters a processing pipeline where classification, language adaptation, summarization, SEO, category mapping and duplicate checks are applied. The orchestrator tracks the workflow state and ensures that each article passes through the required steps before it becomes eligible for publication. This creates a controlled content-processing layer between the external data source and the publishing layer.

Keeping an editorial checkpoint inside automation

Most of the news operation runs automatically. However, when the system determines that an article requires editorial review, it is removed from the automatic publishing path and routed to a human editor. This reduces manual workload in high-volume publishing while preserving human intervention for exceptional content.

Managing multiple news websites from one central system

The platform is actively used across five different news websites. Each publication can be configured according to its own category structure and content preferences. This preserves a shared news source and centralized processing infrastructure while allowing the final publishing output to differ by site.