Through natural language understanding, we improve the process of content creation and how it is consumed. We do so by automating internal workflows and applying semantic tagging and metadata enrichment to categorization, data linking and entity extraction. This makes it easier for your users to discover and navigate information of interest, extending the value and shelf life of your content.
We also augment the editorial process and reduce the manual effort of your teams by streamlining the cross-checking of sources and document comparison.
Our solutions have been chosen by some of the industry’s leading publishers.
Solutions of NLU for Publishing & Media
Taxonomy Management and Editorial Content Enrichment
Increase the monetization and shelf life of content through entity extraction, semantic tagging, data linking and metadata enrichment.
Automatic Article Categorization
Categorize content by topic based on our rich, out-of-the-box vertical taxonomies or create customized taxonomies that are easily implemented via machine learning.
Increase user engagement with contextual content experiences and targeted recommendations by understanding audience consumption, behaviors and trends.
Leverage natural language processing to analyze large databases, capture trends, identify missing links and expand and improve fact-checking.
Newsroom Productivity Management
Accelerate reporting, integrate news and trends from social media and other sources, identify and filter fake news and improve audience engagement by applying NLU to your information streams.
Deliver compelling user experiences, create differentiated data products, and operate more efficient workflows to provide the up-to-date and actionable intelligence needed to guide decision making.