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VerifiedSoftware Development· Founded 2020

Changeaerial

ChangeAerial’s software exploits IP helping organizations transform how they inspect infrastructure. If detection is a key inspection objective, how do companies measure success? RSI©-enabled drone software helps organizations detect more asset anomalies with greater accuracy and scalability. Our software reduces aerial inspection costs by > 40% with > 40% more capacity, and can be deployed and integrated into monitoring programs delivering productivity value in weeks. Organizations detect more augmenting workforce intelligence with actionable insight driving new quality & cost value streams that measurably improve assets lifecycle performance with > 10x ROI. RSI© tools may be the only practical means for enabling large-area monitoring further enhanced with BVLOS & autonomous docking stations. Existing drone approaches endure inherent detection efficacy, speed, cost, & capacity performance constraints. Achieving accurate high confidence autonomous anomaly detection from non stationary image collection routines requires a different approach to existing practices. While numerous AI & even deep learning damage detection tools are becoming commercially available, they require thousands of anomalous training images. They are fueled by image data captured through manual flight with subsequent analysis of single-time images incapable of detecting damage associated with apparatus deformation or fine-scale damage. Our end-to-end digital approach & use of novel deep learning algorithms to exploit time-sequential images deliver more efficient, precise asset monitoring to improve performance compared to single-time, manual & AI-based approaches currently offered by competitive drone software platforms. Take an RSI© PoC monitoring challenge. Access ChA software to prove the costs & revenue benefits gained from autonomous detection. info@changeaerial.com

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HeadquartersSan Diego, United StatesEmployees7(1 to 10)Founded year2020Websitechangeaerial.comLinkedIn profileLinkedIn

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