Text AI Services for Publishers

Text AI Services for Publishers

Our Text AI Services for Publishers provides automatic classification, entity extraction, relationship extraction, and recommendations.

Our Text AI Services were originally designed to meet the challenges of automated content workflows in the publishing industry, and are ideally suited to AI classification and automated tagging of news, sport and entertainment content.

Why do publishers tag their content?

Most large publishers need to tag or classify their content for a number of reasons :

  • to assist internal processes and work-flows
  • to improve search and discovery
  • to provide richer content and user analytics
  • to drive advertising
  • to deliver richer user experiences

Typically tagging is a manual task, integrated into the editorial workflow and the CMS. Increasingly, publishers are working to automate this process using NLP and machine learning techniques.

Automated content tagging

Automating content tagging unlocks a lot more value, as the automated-tagging system can be used to

  • improve tagging efficiency, consistency and quality on the news desks
  • fully-automate tagging of external news feeds
  • unlock value in long-tail content
  • automate tagging of other content around the organisation

For this reasons, publishers are investing large sums and time in building their own automated tagging systems. However what may seem like a simple problem in the R&D labs can turn into a much more complex and expensive problem, when put into production.

How Data Language Text AI Services can help

Our Text AI Services are an AI and Machine Learning fully managed SaaS product. We built them to make it as simple as possible to integrate automated tagging and classification into your publishing systems, addressing all the key challenges :

  1. It is incredibly easy to integrate. Send it content to learn. Send it content to tag.
  2. It uses your own dictionaries, taxonomies, and classification vocabularies out of the box.
  3. The engineering challenge of scaling, retraining, and efficiently redeploying the machine learning models is done for you.
  4. It learns on the fly. As new terms arise in news, our Text AI Services learn them quickly.

Total cost of ownership

Building you own AI based tagging solution is no mean feat. It is not just a data science problem, but involves software engineering, testers, DevOps, infrastructure, scaling automation, model deployment automation, continuous machine learning model training automation, as well as the project management and business processes that accompany a project of this nature. Both the total cost of ownership and time-to-deliver is substantial.

With our Text AI Services you can be up and running in hours, not months, at a fraction of the total cost and you can put your data scientists to work on your market differentiating data outcomes instead.

Get in touch

Use the contact form to get in touch - we are here to help.

Our Products

Text AI Services
Text AI Services
Our best-in-class Text AI SaaS Services solve the common pain points at scale in Text Classification, Entity Extraction, and Content Recommendations.
Sky

Data Language have great experience in information architecture for broadcasters, which is quite rare. Their enthusiasm has rubbed off on my team, which is a real bonus.

Head of Recommendations and Metadata, Sky TV
Oliver Bartlett
Get In Touch

Frequently Asked Questions

What are Data Language Text AI Services?

Data Language Text AI Services are commercial SaaS tools for sophisticated, language agnostic text classification and recommendation using AI and machine learning. They are fully managed cloud services, that use your own dictionaries, taxonomies, vocabularies or knowledge graph entities. They are built on pure machine-learning algorithms and thus avoids problems such as disambiguation. They are self-optimizing, and evolve as your content evolves.

What languages do Data Language Text AI Services support ?

Data Language Text AI Services are language and character set agnostic. They work out-of-the-box on all latin character set languages, as well as Cyrillic, greek, Arabic, and any other alphabet based language. They have not yet been deployed on Chinese and Japanese Kanji, but if you have a project for classification of Kanji text, we would be happy to work with you.

How do I integrate Data Language Text AI Services with my publishing system ?

Data Language Text AI Services are incredibly easy to integrate. They have powerful APIs for training and prediction. Documents are sent to the training endpoint for on-the-fly training, and sent to the predict endpoint for sub-second rapid prediction. We also have a visual playground that can be used for experimenting, and trialling the services. All the infrastructure is managed by us, you can be up and running in just hours.

How does your AI Text Classification work?

Our Text AI Services are pure machine learning AI. They learn on-the-fly as you feed tagged content into the API, and then will tag fresh or un-classified content from what is has learned. As such our Text AI Services not only learns your terms, but also the style of your teams' classification. Also - they do not suffer from disambiguation problems, as they know the difference between turkey and Turkey, because you do.

Technically our Text AI Services train a set of machine learning models automatically as you send in content, self-tune and optimise these models, and update them on-the-fly. They also continually self-improve and evolve as your content evolves.