AI & Automation
Computer Vision & Automation
6–16 weeksVisual inspectionDemo
Object detected & countedAnomaly detected
Objects detected
5
4 good · 1 with a defect
Accuracy
98.7%
hits per type (mAP)
Speed
60 fps
real-time inspection
Automate what your teams see but can't scale: defect detection on production lines, product classification, object counting, and real-time video analysis.
What once required dozens of manual inspectors becomes a system that operates 24/7 with consistency and full traceability. Technically: object detection models (YOLO, DETR), classification (EfficientNet, ViT), semantic and instance segmentation, and inference pipelines for batch or real-time operation on cloud, edge, or private infrastructure; with per-class metrics report (precision, recall, F1, mAP).
Use cases
- —You need to detect defects or visual variation that currently depends on manual review
- —You want to classify products, crops, parts, or materials from images
- —You need to detect objects, counts, or events in images and video
- —You want to analyze behavior, traffic, or activity through cameras
- —You need to segment scenes, areas, or components for visual measurement and control
Deliverables
- —Trained model with per-class metrics report (precision, recall, F1, mAP)
- —Image-to-JSON inference API for batch or real-time operation
- —Annotation and labeling workflow with quality guidelines
- —Hardware sizing recommendations for inference
- —Camera, API, or existing system integration
- —Technical documentation and operations guide