High accuracy annotation for computer vision and AI models. We transform raw data into ground-truth intelligence.
Poor labels reduce model performance. Inaccurate annotations create a cascading effect of errors, leading to biased, unreliable, and ultimately failing AI models in production.
Structured annotation workflows with multi-tiered QA checks. We deliver 99.9% accurate ground truth data by combining specialized human expertise with automated validation.
Tight object localization for standard CV tasks.
Skeletal modeling and pose estimation data.
Pixel-perfect polygon approximations.
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Discover how Engai's Data Pipeline and AI Infrastructure platform can make your organization AI-ready:
Automatically discover and map all datasets with contextualized inventory
Effortlessly manage ML lifecycle and address governance gaps
Drastically reduce deployment time by mitigating edge-case risks
Immediately detect and respond to model drift to minimize threat impact
Proactively apply zero-trust protection mechanisms for proprietary data
Your requirements and proprietary sample assets are encrypted in transit and never used for public model training.
We support bounding boxes, polygons, polylines, keypoints, semantic masks, instance masks, classification labels, and temporal annotations for video. Output formats include COCO, Pascal VOC, YOLO, CVAT XML, JSON-L, and fully custom schemas tailored to your model architecture.