Creating a customized semantic space has never been so easy

Unsupervised machine learning methods are used to train the Retina’s semantic body of knowledge. has created several standard Retina Databases that can be refined to create domain- and jargon-specific databases using reference material (encyclopedias, ontologies, dictionaries), web content (by using semantic crawlers) or any other relevant text data.

Retina Databases at a glance

  • Any language or business domain
  • No large training data sets required
  • Extension to the Retina Engine
  • Training via unsupervised machine learning
  • Easy and transparent optimization by domain/business experts

How does it work?