Apparatus and method for aggregating and evaluating multimodal, time-varying entities

A non-transitory computer readable storage medium with instructions executed by a processor to:

• receive from a network connection different sources of unstructured data, wherein the unstructured data has multiple modes of semantically distinct data types and the unstructured data has time-varying data instances aggregated over time;
• form an entity combining different sources of the unstructured data;
• create a representation for the entity, wherein the representation includes embeddings that are numeric vectors computed using machine learning embedding models;
• infer a property of the entity to form an enrichment with an attribute characterizing the entity;
• repeat the operations to receive, form, create and infer to form an aggregation of multimodal, time-varying entities and a corresponding index of individual entities and corresponding embeddings;
• and
• perform proximity searches on embeddings within the index.