Genus is a text classification and semantic annotation system. Designed to automate recurring tasks in information management, the platform allows you to analyse natural language texts, automatically assign predefined categories based on customer requirements, and identify entities of interest in the texts, such as people, places, dates or specific concepts of interest, which can be customised according to the application domain.

 

Traditionally, these activities require human intervention or rigid systems that are not so adaptable to real-world contexts. Genus overcomes these limitations with a flexible approach: it learns from user-provided data, adapts to the application domain, and can be easily integrated via API into existing platforms and workflows.

 

The system is designed for contexts with high document density, such as public administration, the legal and tax sectors, but also customer care, where it supports classification, registration and indexing processes.

 

Thanks to the combination of machine learning and knowledge representation, Genus allows large volumes of text to be processed in a scalable and consistent manner, transforming unstructured data into organised, ready-to-use information.

 

Created to meet specific operational needs, Genus’ approach can be extended to any domain where unstructured textual data needs to be classified, organised and made intelligible.