AI for vision & measurement
Deep learning designed for the conditions our clients actually face.
We design deep learning systems for industrial vision tasks — detection, segmentation, recognition, comparison. Models are trained for real operating conditions: variable lighting, reflective surfaces, partial occlusion, low contrast, and the optical specifics of subsea imaging.
What we do
Identification and pixel-level delineation of objects, defects, anomalies and regions of interest in industrial imagery.
Models trained to recognise meaningful differences between an observed image and a reference — going beyond simple pixel-level subtraction.
Training pipelines and data augmentation strategies designed for real-world conditions: lighting variation, glare, occlusion, low contrast, turbid water.
From lightweight on-device inference to high-resolution server-side analysis, depending on operational constraints and available infrastructure.
Method
Define the visual task and what success looks like, quantitatively.
Curate data, augment for field conditions, train with traceable metrics.
Cross-validation, error analysis, robustness testing.
Inference pipeline, monitoring, model update strategy.
Typical applications
Automated visual control of parts and assemblies on manufacturing lines.
Detection of unexpected items or non-conformities in complex visual contexts.
AI-assisted analysis of ROV imagery for offshore and subsea industrial assets.