Agent-based searching over heterogeneous data sources

Abstract

Searching heterogeneous cybersecurity data sources is described. A natural language search enables searching across available data sources, independent of underlying storage architectures or query languages. This capability leverages multiple task-specific agents, large language models, and data map representation-based approaches, and enables integration of new data sources into the search process with minimal additional computing resources. The searching includes determining a data map representation for available data sources (which might have different storage architectures or query languages), which indicates relationships between the available data sources. Query intent associated with a query is determined. A query intent task is determined by mapping the query intent to a relevant data source according to the data map representation. A search agent parameterized for searching the relevant data source executes the query intent task. The result of this executed query intent task is used to augment a response to the query.