iEagle AI

Built for Real NDT Conditions

Unlike generic image-recognition systems, iEagle AI is designed around the conditions of real NDT inspections. The solution can integrate inspection methods, surface conditions, UV-A lighting, image acquisition, indication characteristics, acceptance criteria, expert-reviewed inspection data, and traceable quality records

This approach helps bring AI closer to the actual inspection process rather than treating inspection images as standalone data.

Practical AI Integration

iEagle AI can be integrated with inspection equipment, industrial cameras, UV-A lighting, image timing, HMI systems, and review interfaces.

A controlled implementation approach allows manufacturers to validate AI performance using real components and expert-reviewed inspection data before expanding to AI-assisted automation.

Key Benefits

• More consistent first-level inspection and screening
• Reduced repetitive visual review for inspection teams
• Support for higher production volumes
• Expert-reviewed AI training and validation
• Scalable from assisted inspection to validated automation

AI Capabilities for MPI & FPI

NG Judgment & Classification

Support validated NG judgment, defect type classification, and NG category output.

Anomaly Detection

Identify unusual visual patterns and potential indications, including applications where defect samples are limited or classification criteria are still being established.

Defect Localization and Marking

Mark suspected indication locations and relevant image regions for operator review, quality records, and downstream processing.

OCR & Code Recognition

Read part numbers, serial numbers, batch codes, labels, and other production identifiers to connect inspection results with individual components.

From Inspection to Quality Data

iEagle AI connects equipment, AI results, part information, operator reviews, and reports into a traceable workflow.

After validation, AI-assisted results can support:

• NG  judgment
• Defect classification
• Review records
• Quality reports
• Sorting logic
• Inspection traceability

As verified inspection images and results accumulate, manufacturers can build a stronger inspection database for ongoing process improvement and AI model development.

AI Vision Beyond NDT

In addition to MPI and FPI applications, iEagle AI can support a range of industrial visual inspection tasks, including surface inspection, appearance checks, identification, verification, measurement, and automated quality-control processes.

Industrial AI Vision Applications

Defects & Appearance
Surface defect detection, appearance inspection, and visual quality assessment.

Identification
OCR, barcode and QR code recognition, part identification, serial numbers, and batch codes.

Verification
Part presence, position checking, orientation review, and assembly inspection.

Measurement
Visual dimensional checks and feature matching.

Automation
NG classification, sorting logic, and automated quality workflow integration after validation.