“We transfer the latest research and development advances in data retrieval, analysis, annotation and linking into the media and content industries.”

Company Description

MODUL Technology GmbH is your partner in innovative solutions for media and data collection, annotation and linking, integrating extracted and external knowledge into existing workflows and powering new and extended user interfaces and applications such as: news event or topic detection, social media retrieval and organisation, TV/video enrichment with related information and content.

As a research and innovation spin-off of MODUL University Vienna, the Technology GmbH enables university faculty (as the technology experts) as well as hired researchers and developers to work on near-to-market R&D with a close collaboration with the University itself and support existing and future University spin-offs.

It was founded in 2015 as part of the exploitation plans of the LinkedTV project, in order to continue to coordinate LinkedTV technology development and promote it to industry. It has access to technology experts from throughout the Department of New Media Technology, which conducts cross-disciplinary research on knowledge acquisition, semantic Web annotation, human-computer interaction, data analytics, natural language processing and multimedia description and linking. Its first project collaboration has been to develop solutions for news topic detection and social media retrieval in the InVID project, together with its commercial technology partner webLyzard technology.


Linked Television

Link your media to additional information and content easily and powerfully, giving your media consumers a wholly new media experience. 

The Linked Television technology set can analyse your audiovisual content, richly annotate the media in terms of its structure and content and semi-automatically generate links to related information and content about the concepts and topics in the annotation. These links can then be synchronized to media playback, enabling single or multi-screen applications for enhanced media consumption. Let MODUL Technology GmbH co-ordinate your Linked Television project – contact us!


Media Mixer

Technologies to help content owners and others re-use and re-mix their content.

Media Mixer combines the latest, innovative multimedia technologies to enable enterprises to richly annotate their media assets and use those annotations for flexible and powerful media re-use and re-mix scenarios, both internally and making their media available for new uses by third parties. MODUL Technology GmbH offers consultancy, training and technology transfer on the whole set of Media Mixer technologies: media analysis, annotation, fragmentation, rights management and asset organisation.

First MODUL Technology project: welcoming In Video Veritas (InVID)

MODUL Technology GmbH, which was founded last year, welcomed on the first day of its first new year 2016 its first self-acquired EU research project: In Video Veritas (InVID)!

InVID sets out to solve a very difficult problem: verifying the truthfulness of video content posted on social networks which claim to show news events. News agencies have to repeatedly deal with fake, manipulated or misrepresented videos being spread online in the aftermath of a news story. To retain their viewers’ trust, they want to be sure of the authenticity of such video before using it in their news reporting. InVID will provide a complete toolset, driven by various innovative technologies, to aid journalists and newsrooms in semi-automatically determining if a video is trustworthy or not.

MODUL Technology GmbH will develop in this project the social media data ingestion pipeline. Data ingestion will be driven by in-time news event detection, since at any one time the InVID platform should only be collecting relevant candidate media for the verification process, i.e. videos being posted which claim to show something related to a current news event. Detected events will be appropriately labelled so that a query mechanism which is regularly updated can retrieve candidate media items from the social platforms. These items, in order to allow for user friendly search and browsing in the applications which use the platform data, will be richly annotated according to their content and structure, with a focus on unambiguous entity detection (e.g. for determining the location claimed to be shown in the video). This pipeline will be integrated as part of the InVID project into the webLyzard Web Intelligence Platform, which forms the core of the InVID platform solution.

MODUL Technology’s news event detection and dynamic social media querying components can help drive any organisations data ingestion needs, e.g. for online media monitoring as part of a Marketing Intelligence approach or for social media browsing as part of an UGC re-use strategy on a Website or a social network channel. Let us work it out for you, contact us now!


In video veritas, if we divert the old Latin saying: In video, there is truth! The digital media revolution and the convergence of social media with broadband wired and wireless connectivity are bringing breaking news to online video platforms; and, news organisations delivering information by Web streams and TV broadcast often rely on user-generated recordings of breaking and developing news events shared by social media to illustrate the story. However, in video there is also deception. Access to increasingly sophisticated editing and content management tools, and the ease in which fake information spreads in electronic networks requires reputable news outlets to carefully verify third-party content before publishing it, reducing their ability to break news quickly while increasing costs in times of tight budgets.

InVID will build a platform providing services to detect, authenticate and check the reliability and accuracy of newsworthy video files and video content spread via social media. MODUL Technology provides solutions to detect news events from social media streams and collect references to videos posted on social networks that claim to show those events for verification.



ReTV aims to provide broadcasters and content distributors with technologies and insights to leverage the converging digital media landscape. By advancing the start of the art in the analysis of this media landscape and providing novel methods to dynamically re-purpose content for an array of media vectors (= all relevant digital channels), a Trans-Vector Platform (TVP) will provide these stakeholders with the ability to “publish to all media vectors with the effort of one”. It will empower broadcasters and consumer brands to continuously measure their brand reputation, and to compute success metrics that predict reach and audience engagement of content and advertisements across vectors. This will allow editors, program planners and communication managers to optimize decision making processes.

MODUL Technology will provide the innovation solutions for structured media content annotation and content-based recommendations using predictive analytics.


Meet the Team

Technology projects are handled by:

Dr. Lyndon Nixon (CTO) brings his more than 15 years of R&D experience to MODUL Technology projects, defining and developing new innovations in media annotation, linking and re-use. His experience includes scientific coordinator for the LinkedTV project and project coordinator of several EU and national projects including MediaMixer.  He is  currently Workpackage Leader in the InVID and ReTV projects.
  Maximilian Lang (Project Manager) ensures a smooth execution of our projects from kick-off through to the successful conclusion. He has experience administrating many EU and national research projects.
  Rod Coronel (researcher) works in the InVID project on social media content ingestion.
Fabian Fischer (researcher) works in the InVID project on the NLP pipeline, keyword extraction from text and capturing lexical knowledge.
  Daniel Fischl (researcher) works in the InVID project on news story detection from social media streams and the UI/UX for the browsing/visualisation of news stories
  Stefan Gindl (senior researcher) joins the new ReTV project as an expert in content recommendation / prediction systems

What we offer


  • Consultancy. Find out your media content and metadata requirements and how innovative technologies can help you better manage, re-use and enrich your content!
  • Technology transfer. We develop concepts and demonstrators for you, configure and customise the technology you need and can create a full end-to-end solution for your data and media needs.
  • Knowledge transfer. We can train your staff in new media technology or offer remote support from our experts.


  • Topic detection from data streams.
  • Data retrieval based on real-time changing topics
  • Online and social media content collection
  • Rich media annotation including entity recognition and linking to resources in public Knowledge Graphs (DBPedia, WikiData etc.)
  • Media linking and browsing, including semantic search, faceted navigation and semantic similarity measures

Contact us


MODUL Technology GmbH

Am Kahlenburg 1

1190 Vienna, Austria