Vyasa’s Neural Concept Recognition AI technology can train on concept types (e.g. drugs, diseases, pathways, conditions, side effects, genes) in structured and unstructured content. Once trained Cortex builds a dynamic knowledge graph of everything know about those concepts across all of the sources it has been given access to. Because everything in Cortex is converted into a vector space, each concept in the knowledge graph is connected to everything else in vector space. This allows users to query Cortex for connectedness and proximity of concepts across very large knowledge sets thereby yielding unexpected relationships between mechanisms of actions and disease conditions that might be otherwise missed. This type of connectedness analysis is an excellent tool when evaluating potential drug repurposing and target finding.