AI Is in the DNA of Our Services

Retriever and Our AI Powered Solutions

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Experience Unrivalled Media Monitoring and Analysis Tailored to Your Needs

At Retriever, we've been leading the way in AI-driven media monitoring and analysis long before the current AI trend. We like to think of AI technology as part of our DNA – a key part of who we are and the services we offer.  

With years of expertise and dedication, we're proud to call ourselves pioneers in the field. Today, we offer unmatched AI-driven services tailored specifically to you and your business.  

A Pioneer on the Nordic Market 

We are committed, and have been for years, to developing and rigorously testing language models tailored exclusively to the Nordic languages. That way, we ensure that we deliver exceptionally precise and thorough media monitoring and analysis to our Nordic-focused customers. 


AI Powered Communications Analytics That Deliver Tailored Insights

Our AI analytics tools are designed to be client specific. That means that you are guaranteed to get refined insights that meet your specific needs and goals. Conventional sentiment analysis can be applied universally but tends to deliver generic insights. We specialize in tailoring sentiment analysis specifically for your company.  

Instead of only relying on generic content classification, such as IPTC categorization, a standard in the industry, our analysis services empower you as our customer to categorize your content according to your own unique requirements and definitions.     


Get Access to Unique Market Leading Data Thanks to AI 

AI tools only shine when they have access to the right data. One of our core strengths is our extensive Nordic media coverage – giving our AI tools access to unique, market-leading data.  

During our 20+ years as a leading media monitoring agency, we have built the largest digital news archive in the Nordics. Our database contains enormous amounts of data from the Nordic and international media landscape, from both editorial and social media sources. And millions of new articles and posts are added every day.  

 Through our partnership agreements with the important media and media houses, we receive access to article content in source format, full text and texts from behind pay walls without jeopardizing media copyright.


Redefine Efficiency With AI and Our Team of Experts  

Our AI powered tools help streamline your media monitoring and analysis processes, making it easier to extract valuable insights you might otherwise miss. From language detection to semantic similarity, we've developed cutting-edge solutions that improve your monitoring.  

But technology is just one part of the equation. We believe in combining cutting-edge technology with human connections and personalized service. Our team of experts work closely with you to understand your unique needs. This approach allows us to provide you with invaluable insights and strategies to optimize your communication efforts, strengthen your brand presence, and foster enduring customer relationships. 


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Why choose Retriever?


Gain a Competitive Edge

With our AI's comprehensive language support and tailored analysis, you’ll be able to make informed decisions that set you apart from the competition. 


Save Time and Resources

Our efficient AI applications help you save time, reduce manual work, and focus on what matters most – making sense of the data and making well-informed decisions. 


Uncover Hidden Insights

Our semantic similarity and anomaly detection tools uncover valuable insights that might otherwise go unnoticed, enabling you to react proactively to changes in your media landscape. 


Get to know the AI applications at Retriever

Entity extractions

Our tools automatically perform entity extraction on all editorial content. This feature is particularly useful for reducing search result noise. For instance, when searching for "Retriever," it might yield documents related to dogs. However, searching for the organizational entity "Retriever" will effectively filter out articles about dogs and retain documents related to the company "Retriever." Another common application of entities in Retriever is conducting quantitative and qualitative analyses of media coverage for specific individuals or organizations.

Global, general, and customer-specific classifications

Access automated categorisation of articles within a wide range of categories. We implement IPTC categorisation on all our editorial articles, and these categories can be used as search filters, in the same way as entity filters. The categorisations are customised to meet the specific needs of our customers and are developed at the request of our experts.

General categories are used for common analyses, such as sorting editorial content as "news" and "opinion." The first category represents fact-based content, while the latter reflects an individual point of view.

General and Entity-Based Sentiment analysis

Over the years, we have created machine learning models that identify sentiments in social media posts. With our social media listening tool, Listen, you can analyze the overall sentiment trends across entire segments of social data and make side-by-side comparisons.

We also offer entity-based sentiment models that extract sentiments specific to organizations or individuals mentioned in editorial articles.

Language detection

The language filter is a critical aspect of content searching, particularly for online sources where language cannot be easily determined by specifying the source. Now, you can automatically identify a wide range of languages with our language detection tools. The tools are developed specifically for the Scandinavian languages, allowing us to distinguish them despite their similarities even in short texts, such as tweets on Twitter/X.

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Semantic similarity

Semantic similarity determines the likeness of different texts in terms of content. This helps in grouping related articles within search results, for example, articles that cover the same story but come from different media sources. Grouping them together saves users time and streamlines analysis tasks.

Another area where we apply semantic similarity is in press release tracking. Our tools automatically identify which articles are derived from press releases, enhancing the efficiency of press release analysis.

Keyword extractions

Keyword extraction involves the automatic identification and extraction of significant words or phrases from text. Its purpose is to offer a summary of the content and help users quickly get an overview of the main topics.

We have developed machine learning models for keyword extraction from social media posts. Listen, our social media listening tool, uses these features to analyze and compare various social segments, which may include our client’s competitors or any custom-defined search topic.


Speech-to-text, also known as speech recognition, is the process of transforming spoken language into written text. We use speech-to-text machine learning models to convert a variety of spoken content, like TV and radio broadcasts, podcasts, and YouTube videos, into text.

This type of conversion makes spoken content accessible and searchable. Once the spoken content is in text format, we can analyze it in the same way that we do with regular text content.

Anomaly detection

Identify unexpected and significant changes within the social media segments you are monitoring with our anomaly detection algorithms. These changes include sudden increases or decreases in the number of social media posts that match specific search criteria or surges in engagements.

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