ScavAI leverages computer vision technology to detect critical faults, such as carbon deposits and oil leaks, during scavenge inspections. With automated image analysis, ScavAI accelerates the inspection process, improving accuracy and minimizing human error. The system automatically identifies key fault types to prevent system breakdowns and enhance maintenance efficiency. By streamlining inspections with image analysis, ScavAI eliminates manual checks and improves report verification. Future versions will include predictive capabilities, allowing you to foresee potential faults before they disrupt operations, ensuring proactive maintenance. This predictive maintenance, currently in development, will use trend analysis to predict potential faults, enabling early interventions and reducing downtime. By automating the inspection process, ScavAI minimizes mistakes in maintenance verification, ensuring accurate and reliable results.

Features:

• Proactive Fault Detection: Automatically identifies 8 key fault types, such as carbon deposits and oil leaks, to prevent system breakdowns and enhance maintenance efficiency
• Automated Inspection Process: Streamlines inspections with image analysis, eliminating manual checks and improving report verification
• Predictive Maintenance (In Development): Predict potential faults using trend analysis, enabling early interventions and reducing downtime
• Reduced Human Error: Minimize mistakes in maintenance verification by automating the process, ensuring accurate, reliable results