Deep-Ai provides AI-driven non-destructive testing (NDT) solutions that utilize automated evaluation techniques to enhance the accuracy and efficiency of inspections. By addressing human error in traditional testing methods, Deep-Ai reduces inspection time by 50% and costs by 53%, while achieving a 97.1% accuracy rate in defect detection.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional non-destructive testing (NDT) methods are prone to human error, leading to inconsistent and potentially inaccurate inspection results. Manual evaluation of large datasets from techniques like eddy current testing (ECT) is time-consuming and costly. These limitations hinder the efficient and reliable detection of defects in critical industrial components.
Solution
Deep-AI provides AI-powered solutions for automating non-destructive testing, enhancing the accuracy and efficiency of defect detection. Their technology leverages deep learning algorithms trained on extensive datasets to analyze inspection data, reducing the reliance on manual interpretation and minimizing human error. Deep-AI's solutions offer automated signal acquisition and analysis, enabling faster and more consistent identification of anomalies in various industrial assets. The platform supports multiple NDT methods, including ECT and ultrasonic testing (UT), providing a comprehensive approach to asset integrity management. By automating the evaluation process, Deep-AI reduces inspection time and costs while improving the reliability of defect detection.
Target Audience
Deep-AI's primary customers include companies in the power generation, oil and gas, chemical processing, and manufacturing industries that require reliable and efficient non-destructive testing solutions for asset integrity management.
Features
- AI-driven analysis of ECT signals for automated defect detection and characterization
- Support for multiple NDT modalities, including ECT, IRIS (Internal Rotary Inspection System), ultrasonic testing (UT), and motion amplification
- Automated signal acquisition using collaborative robots for consistent data collection
- Advanced data analytics and visualization tools for comprehensive inspection reporting
- AI algorithms trained on over 20 million data points for high accuracy
- Solutions for specific applications, including steam generators, heat exchangers, and pipelines
- Integration with robotic systems for automated inspection workflows
- Cloud and on-premise deployment options to meet customer security requirements