Our experience and many successful projects have shown us that metadata is a crucial next step in the digitalization in the media industry. Let our passion for metadata and publishing help you reach your digital goals. Scroll down for more information on our existing and future solutions.




The language-independent AI solution enables more time for journalists to focus on their primary task; writing. At the same time, it provides better quality data that improves decision-making, and opens up opportunities to build new products and services.

Our solution automatically checks your articles for suitable tags and prepares them for publishing on the web. As you write, it generates the correct metadata in the background, including the most relevant tags to optimize contextualization. High-quality and consistent metadata provides a foundation for recommendations, automation, and personalization, as well as improving SEO and reach.

Pilot study

Historical tagging

Live auto-tagging

Gender analysis

Automation & personalization

Our solutions enable automatic or semi-automatic processes that provide a personalized user experience and improve publishing efficiency. Recommendations, automated landing pages, concept (topic) pages, personalized news feeds and newsletter integration are all important parts of this. Benefits include more loyal users, more efficient work processes and increased SEO reach.

We offer a recommendation system that can be used to provide the classic “You might also be interested in” experience based on editorial input (news value), contextuality, popularity and personal interest. This service can easily be extended to help with automated landing pages.

On top of this we are assisting our customers with concept (topic) pages, personalized news feeds and newsletters. If you are interested in working with us on these areas at an early stage and would like to influence our development strategies, please reach out!


Topic pages


Personalized article feeds

Personalized newsletters


We want to help our clients by providing an excellent way of consuming more content for their readers. Our recommendation engine is customized for the news industry and built upon seven parameters that we believe are a unique blend for enhanced news consumption.


Geographical closeness
Often there is a location associated with a news story, and the story is naturally more relevant to people that live close to this location. The feature of geographical closeness promotes articles with an associated location nearby to individuals.

Closeness in time
News agencies produce a large number of articles every single day. Some articles have a short life span and are relevant only for a short time after they have been published. Other articles may be relevant for days or even weeks after publication. The feature for closeness in time promotes articles that are still relevant based on the age of the articles and when it is consumed.

In our experience, the personalization feature for article recommendations is a very important one. The personalization feature models a user’s interest in different kinds of content and a user’s actual read history of articles. This is the feature that ensures a user is recommended articles the user is evidently interested in.

Editorial news value
News editors often deem certain articles to be more important and of interest to the general public. This is sometimes indicated by an article’s news value set by an editor. Our recommendation service takes into account the editorial input for news value.

Recommendations often are presented adjacent to an article, and the context for a recommendation is determined by this surrounding content. For example, a sports article and a lifestyle article define two different contexts. Our recommendation service takes into account the context in which a recommendation is presented.

Article performance
The article performance measures how many users have read an article during a time. This is the measure that identifies trending content. Article performance is a simple and potent feature that influences the recommendations in our service.

Cultural closeness
The principle of Cultural closeness is about the content being relatable. If you can personally relate to a piece of content, it is much more likely to be perceived as attractive.

Content & audience analysis

Auto-tagging is really a means to an end. Tags enable you to understand your content and analyze it; mixed with user data, you get valuable insight about your production and user consumption patterns. With these insights, decision-making becomes easier and more accurate.

Using iMatrics REST API, it’s easy to import the tags into different systems such as DMPs or data lakes. If questions, issues or ideas arise, our skilled developers and data scientists are ready to help you out. We are used to supporting our customers with data wrangling, clustering analysis and sorting out use cases.

Production insights

User segmentation

Data science as a service

Survey (free-text) analysis


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+46 73 633 15 18


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