Donecle provides an automated drone inspection solution that utilizes image analysis algorithms to detect defects in aircraft, significantly reducing inspection time to under one hour. This technology addresses the inefficiencies and safety concerns associated with traditional manual inspections, enhancing maintenance processes for military and commercial aviation.
Funding
$7.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional aircraft inspections are time-consuming, require significant manual effort, and can be challenging to perform consistently, especially in hard-to-reach areas. This can lead to delays in maintenance, increased costs, and potential safety concerns due to variability in inspection quality.
Solution
Donecle offers an automated drone-based inspection solution that significantly reduces aircraft inspection time while enhancing safety and traceability. The system utilizes autonomous drones equipped with laser technology to navigate and capture high-resolution images of the aircraft's surface. These images are then processed using proprietary image analysis algorithms to automatically detect and classify defects, generating detailed inspection reports. By automating the inspection process, Donecle enables faster turnaround times, improved inspection consistency, and enhanced data management for airlines, MROs, and military operators.
Target Audience
The primary target audience includes airlines, maintenance, repair, and overhaul (MRO) organizations, and military aviation operators seeking to improve the speed, accuracy, and efficiency of their aircraft inspection processes.
Features
- Autonomous drone operation using laser technology, eliminating the need for a pilot or GPS signal
- High-resolution image capture of the entire aircraft surface, including landing gear and engines
- Automated image analysis algorithms for defect detection and classification
- Generation of detailed inspection reports with visual representations of identified defects
- Cloud-based data storage for digital aircraft history and paperless process management
- Integration with existing maintenance management systems
- Capability to perform multiple inspection types in a single drone flight
- Compliance with aviation authority standards, including Boeing and Airbus AMM listings