OSPREY: Multi-INT Contextual Understanding

The use of contextual information to accurately characterize the interaction between entities and their environment is essential to effective decision making, command, and control. For example, contextual cues may differentiate a benign shift of military resources from preparation for hostile amphibious warfare. Automated representation and interpretation of contextual information gleaned from today’s large and growing set of multi-INT data sources remains a critical unsolved problem.Vision Systems Inc. (VSI) with support from STR proposes OSPREY, a novel capability for machine-readable contextual understanding and drilldown. OSPREY offers a flexible and robust semantic framework to understand and reason about the content and context of multiple-source intelligence (multi-INT) and open-source intelligence (OSINT). OSPREY organizes contextual information derived from a variety of data sources into a shared spatiotemporal-aware representation suitable for cross-domain analysis. OSPREY then combines an autonomous reasoning and action agent with a large-language model to power both human-to-machine and machine-to-machine collaboration and coordination. This agent can reason, make decisions, and interact with structured and unstructured multimodal data sources (e.g., OSINT text, imagery, video, audio; GEOINT/MOVINT, IMINT) to synthesize vital context for reasoning and decision-making about emerging maritime threats. The VSI and STR team is uniquely suited to this project, offering unparalleled expertise in machine learning, natural language processing, and remote sensing; extensive experience in the development of innovative software solutions for challenging defense and intelligence problems; and a thorough understanding of the needs of image analysts across the defense and intelligence community.