Providing Data-Driven Decisions
Government agencies must move from reactive responses to proactive decision-making in today’s increasingly complex and interconnected world. The use of data, statistics, and AI/ML to forecast future outcomes and trendshelps enable the data-driven decisions government needs while anticipating potential risks and opportunities. OST’s Predictive Analytics solutions leverage artificial intelligence (AI), machine learning (ML), statistical modeling and simulation, driving mission success, operational efficiency, and risk mitigation strategies.
With OST’s Predictive Analytics, agencies gain clarity, foresight, and control over their mission-critical operations through data-driven insights, delivering a smarter, more resilient future.
Predictive Analytics – Enabling a Better Future
- Enhances decision-making & strategic planning
- Improves operational efficiency & resource optimization
- Strengthens risk management & threat prevention
- Accelerates response times & mission readiness
Lowering Risk. Increasing Confidence
OST provides a full analytics lifecycle; data ingestion, data engineering, descriptive, predictive, and prescriptive analysis and presentation of information and actionable insights for data-driven decision support. Our dashboards and visualization tools simplify complex datasets, making insights accessible to decision-makers at all levels. Unlike others who simply aggregate data, we specialize in aligning structured, unstructured, and real-time streaming data with mission priorities, while eliminating silos. Whether it is detecting fraud, identifying insider and outsider threats, optimizing supply chain logistics, scanning for cybersecurity vulnerabilities, or improving emergency response, all benefit from quicker, data-backed decisions. This mission-first approach makes analytics informative and directly supports mission success.
CASE STUDY:
Predictive Analytics to Defend Space
Challenge
As the space domain becomes increasingly contested, the U.S. Space Force faces a critical challenge: how to detect and counter threats that are deliberately obscured or disguised. Adversaries are turning to sophisticated tactics—camouflage, concealment, deception, and maneuver (CCDM)—to mask their intentions and activities in orbit. These tactics make it difficult to distinguish benign objects from potentially hostile ones, undermining situational awareness and strategic advantage. To stay ahead, the Space Warfighting Analysis Center’s Space Domain Awareness Tools Applications and Processing Lab is focused on unlocking new ways to expose these hidden threats starting with a key indicator: the radar signature of a space object.
Solution
OST leveraged machine learning to predict the expected radar cross-section (RCS) of space objects. By analyzing open-source data and categorizing satellites into “Small,” “Medium,” and “Large” RCS classes, our models accurately forecast how an object should appear on radar. Any discrepancies between prediction and real-world observation can then signal suspicious activity.
Outcome
A powerful predictive tool that enhances threat detection by flagging outliers with unexpected radar signatures, giving the Space Force a sharper eye on orbit and a vital edge in space domain awareness.