Computer Vision
See what cameras miss. Act on it in real time.
From object detection and segmentation to pose estimation and multi-camera tracking, we build production-grade computer vision systems that run on cloud, edge, or embedded hardware. We take models from research benchmarks to real cameras, real latency budgets, and real lighting conditions.
What We Deliver
Object detection & tracking
YOLOv8/v9/v10, RT-DETR, DINO — multi-class, multi-camera, real-time.
Segmentation
SAM 2, Florence-2, CLIP — pixel-perfect semantic and instance segmentation.
Pose estimation
MediaPipe, ViTPose, RTMPose — 2D/3D keypoint detection for body and motion AI.
Video analytics
Multi-camera tracking, person re-ID (DeepSORT), and action recognition.
Quality inspection
Anomaly detection for manufacturing, pharma, and food QC.
Edge deployment
Jetson Orin, Raspberry Pi, OpenVINO — sub-30ms on-device inference.
Use cases by industry
Where teams put Computer Vision to work in production.
Visual defect and anomaly detection on production lines, with edge inference.
Footfall analytics, shelf monitoring, and cross-camera person re-identification.
Pose-based physiotherapy form scoring and biomechanics analysis.
Crop-disease detection and yield estimation from drone and field imagery.
Real-time multi-camera tracking and event detection at the edge.
See it in action
Live demos and sample outputs.
Models, frameworks & tools
Frequently Asked Questions
Ready to start your computer vision project?
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