Implementing AI, deep learning, and computer vision to monitor oil and gas pipelines to detect leakages and cracks in pipelines in remote and risky areas with automatic segmentation tools.
Utilising artificial intelligence and machine learning to map and inspect overhead assets, drive maintenance actionables and develop an optimal cost-efficient operational strategy.
Enabling computer vision models to detect and instance segment cables for visual inspections, i.e. lacking of significant features, structure failure.
Deploying vision systems to inspect solar panels and photovoltaic cells for defects, optimising the speed and accuracy of quality control, and reducing machine downtime.
Using machine learning to detect and resolve wafer defect to improve wafers' yield in high volume manufacturing semiconductor foundries.
Surveying infrastructure with computer vision to acquire detailed and accurate geometric and visual data to incorporate advanced analytics, self-learning and automation to streamline infrastructure management.
Develop your go-to-market product with our no-code MLOps platform that simplifies how computer vision models are built.