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Computer Vision Development
A pharmaceutical company was shipping defective pills. Not many—maybe 1 in 10,000—but enough to trigger a recall that cost millions and damaged their reputation. Human inspectors were doing their best, but at 500 units per minute, some things slip through.
We built them a vision system. Now every single pill gets inspected, 24/7, at 99.8% accuracy. Defects get caught before they ship. The inspectors moved to quality management roles where their judgment actually matters.
That's what computer vision does—it handles the tedious, repetitive visual tasks that humans shouldn't be doing anyway. Defect detection, security monitoring, document scanning, inventory counting. We use YOLO, SAM 3, Vision Transformers, Florence-2—whatever gets the job done in your environment, at your speed, with your lighting conditions.
- Defect detection with YOLO, SAM 3, and Florence-2
- Real-time object tracking and recognition
- Facial recognition and biometric access control
- OCR and document intelligence with Vision Transformers
- Video analytics for security and operations
Computer Vision Development - FAQs
Defects in manufacturing (scratches, cracks, misalignments), faces and license plates, products on shelves, people counting and movement patterns, document text and forms, medical imaging anomalies, safety violations. If a human can see it and make a decision, we can probably train a model to do it faster and more consistently.
Typically 95-99%+ depending on the task and conditions. We test extensively with your actual data, in your actual environment. Lighting, camera angles, speed—all of it matters. We won't promise 99% if your conditions only support 92%. But we'll tell you exactly what's possible and how to improve it.
Yes—we routinely build systems that process 60+ frames per second with latencies under 50ms. We optimize models for edge devices (NVIDIA Jetson Orin, Hailo-8, Qualcomm AI Stack) or cloud GPUs depending on your setup. Real-time alerts, live video feeds, immediate reject signals—whatever your process needs.