Aspersorium

We are building an environmental risk intelligence platform for the maritime industry. It combines satellite detection, AIS vessel tracking, and drift modeling to identify pollution events, predict their movement, and analyze vessel behavior in context.

At its core is a probabilistic risk scoring engine that evaluates each vessel based on multiple signals: proximity to detected pollution, trajectory alignment with drift patterns, AIS anomalies (such as signal loss or route deviations), speed and maneuver behavior near incidents, and historical patterns of similar activity. These signals are fused into a time-persistent risk profile, producing a dynamic trust index that evolves as new data arrives.

Rather than assigning blame, the system quantifies likelihood and behavioral risk, reducing uncertainty for insurers and regulators and enabling faster, evidence-based decisions.

To further improve accuracy, we integrate a lightweight app for smaller vessels, enabling route optimization and pollution avoidance. In return, these users contribute real-world observations, creating a feedback loop that validates satellite detections, strengthens attribution models, and continuously improves the reliability of the risk scores.