Artificial Intelligence for knowledge management
80% of your business data exist in text format and less than 1% of it are used for making professional decisions
are unstructured (Van der Linden, P., 2018)
analyzed for professional decisions (DalleMulle L. & Davenport T, 2017)
Natural language understanding
Our Semantic artificial intelligence technology manages relationships and concepts using NLU instead of words, for a true understanding of documents.
Based on Forensic Linguistic principles, our unique approach can characterize personal writings by HOW the person writes, WHAT the person talks about and the SENTIMENT involved.
Automatic Domain Ontology
For a deeper understanding of the text, we use Ontologies that describe concepts and domain relationships. Our Axones technology can build your ontology from scratch, based on your sector, department and the particularities of your business. Using the data contained in formal dictionaries and example documents, Axones understands the concepts and their hierarchical and horizontal relationships.
We perform disambiguation with our exclusive Semantic artificial intelligence technology. Our results demonstrate that concept’s context and relationships can be used for a high-performance disambiguation.
Our data analysis technology uses mathematical graphs to manage Ontologies. The artificial intelligence then structures the underlying content of documents and their relationships for more efficient knowledge management.
Our Semantic artificial intelligence technology allows us to develop semantic based search engines, which understand user queries, match them with documents and present ranked results for better business management.
Ontology reinforcement and enrichment
We apply Machine Learning to capture knowledge from documents and enrich the used Ontologies. At the same time, documents knowledge management reinforces the connections between the concepts represented in the Ontology.
Our Semantic artificial intelligence returns summaries of documents by understanding and highlighting what is most relevant to capture the whole document’s knowledge. It can summarize a single document or a collection of documents. These summaries can also be conditioned by a user query.
Our Semantic AI technology returns the phrase that best answers the user query, demonstrating its high performance even when millions of documents and data points are analysed.