OrbitalShield aggregates data from multiple sources, including satellite telemetry, launch environment conditions, and launch vehicle performance.

The collected data is fed into AI-driven predictive models designed to evaluate risk dynamically, accounting for new vehicle types and mission profiles.

The platform operates in real-time, updating risk assessments and recommended insurance pricing continuously.

Insurers and launch providers can access the platform to gain insights and derive optimal policy structures and pricing strategies, effectively reducing the information asymmetry in underwriting space launching risks.

By using real-time data and AI, OrbitalShield reduces insurance premiums and boosts policy accuracy, ensuring that both overpricing and underpricing are minimized.

It enhances transparency and trust between launch providers and insurers, potentially unlocking more affordable insurance coverage for smaller or newer providers, fostering industry growth.

The platform leverages existing data infrastructure and modern AI techniques, though overcoming data sharing reluctance and standardizing data from different providers are challenges.

Medium development costs are anticipated, with some regulatory barriers in integrating diverse, proprietary data sources into a unified platform.