EXAMPLES

Defect Detection

We detect surface defects such as scratches, cracks, and inconsistencies
in materials using custom-trained vision models.

The model is trained on synthetic data and validated on real-world images
to ensure reliable performance in your specific setup.

Presence Check

Verify that all required components are present in an assembly. Detect missing or misplaced parts in real time.

Classification

Categorize products based on visual characteristics. Used for sorting, quality grading, or downstream automation.

These examples demonstrate how custom computer vision models are applied to real-world inspection tasks.

Models are trained to detect specific patterns such as
defects, missing components, and visual differences between categories.

In many industrial environments, collecting large datasets of rare defects is difficult.
These models are designed to work effectively even with limited data.

Typical outputs include bounding boxes and classification labels, providing clear and practical results.

Each model is built and validated for a specific use case, ensuring relevance to real production conditions.

If your task involves visual inspection, defect detection, or classification,
a custom model can be built and tested quickly to evaluate feasibility.