Fleet monitoring across multiple lessees, operators, and jurisdictions is fragmented. Lessors rely on self-reported utilisation data, periodic MRO updates, and manual spot-checks. By the time a stress signal surfaces, it is already a problem.
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.
Which of my A320s haven't flown in 21 days?
3 tails match. N4021 — last seen Sharjah (OMSJ), 24 days ago, operated by Sky One, 38% utilisation over 90 days. N4055 — last seen Tbilisi (UGTB), 22 days ago. N4090 — last seen Lagos (DNMM), 21 days ago. Full per-tail history attached.
Detect early indicators that a lessee is struggling — reduced utilisation, unusual routes, grounding patterns — before it becomes a default or repossession situation.
Show me any of my A320s that have had less than 40 flight hours in the last 30 days across all operators.
Identify aircraft from your portfolio that have been on the ground longer than expected with no maintenance or operational justification.
Which of my Boeing 737s haven't moved in more than 14 days and aren't scheduled for maintenance?
Track when an aircraft from your portfolio changes operator, callsign, or registration — often the first visible sign of a sub-lease or an unreported transfer.
Alert me if any tail in my portfolio changes its operating callsign without prior notice.
Validated with the technical asset-management team at a top-tier aircraft lessor — lessee stress signals, stationary detection, and operator-change monitoring as their three primary use cases.