Safety-critical data for aviation & aerospace.
Assisted and autonomous flight, and aircraft inspection, demand a safety-critical labeling standard with zero annotator drift.
safety-critical · zero drift
The problem
At a safety-critical bar, consistency isn't optional.
Vision systems for assisted and autonomous landing must identify the runway with near-perfect consistency, day and night.
Every runway edge and light string has to be labeled to a safety-critical standard, with zero tolerance for drift between annotators.
How io-ai helps.
Trained experts, an SOP-driven QA pipeline, and rejection-reason metadata on every task, held to over 98% accuracy.
Runway edge & light labeling
Edge polylines by day, light strings & threshold lights by night.
Cabin-interior segmentation
Side-wall, wiring-harness and panel polygons.
Day / night separation
Data split before labeling to keep guidelines unambiguous.
First-batch audits
Audited before scale-up, with rejection reasons on every task.
Modalities & techniques
image
polyline
polygon
Proven work.
A real aviation & aerospace engagement, with a hard number.
Aviation & Aerospace · Image
>98%
accuracy on runway labeling, day and night
Safety-critical runway labeling for assisted-landing AI.
Airbus
Read the case study
Let's talk
Tell us what you're building.
Send us your data challenge and we'll scope a pilot, usually within a couple of working days.