Space Traffic Management AI Platform

Instinct Space develops AI-powered space traffic management (STM) software that goes beyond traditional conjunction screening to provide actionable autonomous decision support for satellite collision avoidance. The company’s platform applies machine learning to historical maneuver data, orbital mechanics, and debris cloud evolution to recommend optimal maneuver strategies that minimize collision risk while preserving fuel and mission effectiveness.

The core challenge in modern STM is the volume problem: a constellation of 1,000 satellites might generate 10,000+ conjunction warning notifications per day from automated screening services. Human operators cannot review and decide on each conjunction; the decision must be automated to a large degree, but the automation must be reliable enough to trust in high-stakes collision avoidance decisions.

Instinct Space’s AI system trains on historical operator decisions, orbital physics models, and statistical distributions of debris cloud positions to develop decision rules that match expert operator judgment in normal cases while escalating anomalous situations to human review. The platform integrates with existing commercial SSA data providers (LeoLabs, ExoAnalytic, SpaceTrack) and sends maneuver recommendations directly to satellite command queues for automated execution.