Underwriters assess risk at policy inception and renewal, but aircraft behaviour changes continuously. Conflict-zone exposure, utilisation spikes, operator changes, and unusual routing happen between renewals and are invisible until a claim is filed.
Wingbits.AI sits on our own network of 6,000+ professionally operated ADS-B ground stations across 120+ countries — live and historical flight data, authenticated at the source. You ask in plain English. No integrations to build, no query language, no API docs to read first.
Has this tail operated in any sanctioned airspace in the last 90 days?
Tail G-ABCD: 2 airspace intersections flagged in the last 90 days. 14 Apr — transited within range of a sanctioned-region designation en route OMDB→UUEE. 2 May — same corridor. Routes, timestamps, and a per-flight risk classification are attached.
Identify whether a specific tail or fleet has operated in or near designated conflict zones, sanctioned airspace, or high-risk regions — at any point in the policy period.
Has tail N789XY operated near any active conflict-zone airspace in the last 6 months?
Detect significant deviations from declared utilisation — a tail flying far more or far fewer hours than the policy basis — which changes the risk profile materially.
Which tails in this fleet are flying more than 20% above their declared annual utilisation rate?
Track undisclosed changes in operator, sub-lessee, or registration that may not be reported to the insurer but are visible in live ADS-B data.
Has the operating entity for tail G-ABCD changed since policy inception in January?
Validated against live sanctions-screening workflows run independently by asset-finance and insurance risk teams — compliance and sanctions monitoring as a high-pull use case.