Computer Vision Solutions

We build computer vision systems for object detection, classification, and visual quality inspection using frameworks like YOLO, OpenCV, TensorFlow, and PyTorch, trained on your own image or video data rather than a generic pretrained model applied as-is. Common applications include manufacturing defect detection on a production line, retail shelf and inventory analysis from camera feeds, and automated visual quality checks that would otherwise require manual inspection.

Model choice depends heavily on the real-world constraint — real-time detection on an edge device (a factory-floor camera with limited compute) requires a different architecture and trade-offs than a batch-processed analysis pipeline running in the cloud, and we scope for the actual deployment environment from the start rather than optimizing a model that later can't run where it needs to.

• Object detection and classification with YOLO, OpenCV, TensorFlow, or PyTorch
• Model training on your own image/video data, not generic pretrained weights alone
• Edge deployment for real-time, on-device detection where needed
• Manufacturing defect detection and automated visual quality inspection
• Retail shelf, footfall, and inventory analysis from camera feeds