Adaptive TEM is built around a proprietary operational evaluation engine designed to deliver structured, measurable, and evidence-based operational threat assessment.

The system continuously analyzes more than 300 million operational data points across airports worldwide using high-quality operational and aeronautical datasets, including FMS-grade aeronautical data derived from Lido’s SkyData infrastructure, together with operational weather, NOTAMs, runway, approach, terrain, airspace, and environmental data sources.

Operational threat evaluations within Adaptive TEM are not generated through probabilistic or generative AI reasoning. Instead, operational outputs are produced through structured operational logic, deterministic evaluation formulas, contextual operational rules, and traceable operational data relationships aligned with Threat & Error Management principles.

This allows operational evaluations and resulting threat outputs to remain:

• measurable
• evidence-based
• operationally explainable
• operationally repeatable
• and traceable down to the individual operational input and evaluation logic involved

Artificial Intelligence is used selectively to support and streamline certain administrative and back-office maintenance processes, such as operational content handling, NOTAM interpretation assistance, and operational data management workflows. AI is not responsible for generating operational threat conclusions or replacing the structured evaluation engine itself.

This architecture ensures that Adaptive TEM maintains operational transparency, consistency, and auditability while avoiding the unpredictability and non-deterministic behavior associated with purely AI-generated operational assessment systems.