AI capabilities

Knowledge representation through ontologies that structure concepts, entities, and relationships in a unified, semantically rich knowledge graph.

Deterministic reasoning through first-order logic over the graph to derive conclusions with formal inferences, guaranteeing explainable and auditable results.

Knowledge discovery through reasoning and logical inferences that identify non-obvious connections between data and equivalent entities.

Discovery through metasearch engines that unify queries across multiple sources, enabling the graph to be explored from diverse perspectives with dynamic visualisations.

Automatic enrichment of information with related data from the knowledge graph, providing multidimensional and contextual understanding of each query.

High-precision profiling based on user interactions and preferences to personalise responses, visualisations, and experience according to specific needs.

Intelligent recommendation through reasoning over the semantic richness of the graph, leveraging deep conceptual relationships and specific contexts.

Dynamic visualisation through real-time interactive representations that transform the knowledge graph into accessible interfaces without requiring technical expertise.

Natural language querying that combines knowledge graphs with generative AI to transform conversational questions into contextualised structured queries.

Identification and consolidation of hidden relationships in unstructured data, transforming texts into formal representations that can be integrated into the knowledge graph.

Reasoning through deep learning and probabilistic techniques to process ambiguous information, identifying patterns and generating predictions in complex contexts.

Automatic classification of content into predefined taxonomies, organising large volumes of information to facilitate efficient navigation and retrieval.

Recognition and disambiguation of named entities in text, transforming unstructured content into structured data linked to concrete entities within the graph.

Metadata enrichment through automatic augmentation with relevant information and duplicate identification via fuzzy matching, improving completeness and eliminating redundancies.

Traducción automática entre idiomas preservando significado y contexto, permitiendo crear grafos de conocimiento unificados que trascienden barreras lingüísticas.

Lemmatisation of words to their base form to improve precision in information retrieval, connecting related concepts expressed through morphological variations.