Building Vision AI pipelines for complex environments.

I build computer vision systems that survive contact with the real world — noisy CCTV, moving dashcams, aerial feeds, and industrial floors where a false alarm costs a supervisor's trust. Over the last 5+ years I have taken projects from data collection and annotation strategy through model training, edge optimisation, and on-site deployment.

The thread across my recent work is the LLM verification layer: pure detection models plateau on precision, so I pair them with vision-language reasoning that re-reads a detection in context before it becomes an alert. That single change is what turned several of these pipelines from demos into systems operators actually keep switched on.