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Share Your Data
Upload raw images, video, text, audio, or LiDAR securely — we ingest from cloud storage, SFTP, or your existing ML pipeline.
Enterprise image annotation services — bounding boxes, polygons, keypoints, and semantic masks with 99.5% QA for computer vision and production ML teams.
Machine learning teams building object detection, segmentation, and visual search models need pixel-accurate labels at scale. Our image annotation services deliver human-verified bounding boxes, polygons, keypoints, and semantic masks for retail shelf analytics, medical imaging, autonomous perception, and enterprise computer vision products.
Noisy labels create false positives in production and slow iteration cycles. We pair domain-trained annotators with written playbooks for edge cases — partial occlusion, glare, SKU variants, and low-light scenes — so your detectors generalize beyond the training set.
Bounding boxes for detection and tracking; polygon and instance masks for segmentation; keypoints for pose and landmark models; OCR and text-region labels for document and shelf vision; multi-class taxonomies aligned to your product ontology.
Retail and e-commerce product recognition, healthcare radiology and pathology, automotive ADAS camera frames, agriculture drone imagery, security person and vehicle detection, and industrial quality inspection on production lines.
Every image batch passes guideline training, blind review, and consensus scoring. We target 99.5% accuracy for safety-critical and revenue-impacting vision workloads, with audit trails your compliance team can review.
Encrypted upload pipelines, access-controlled workspaces, and GDPR-ready handling for global teams. Export to COCO, Pascal VOC, YOLO, or custom JSON — or push annotated assets directly to your cloud bucket or labeling toolchain.
Partner with a data labeling company that ships image datasets your engineers trust. Request a quote for image annotation volume, modality mix, timeline, and QA targets — our project managers respond within one business day.
A proven calibration-to-production workflow for enterprise annotation programs.
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Upload raw images, video, text, audio, or LiDAR securely — we ingest from cloud storage, SFTP, or your existing ML pipeline.
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We define labeling guidelines, class taxonomy, edge cases, and accuracy targets with your ML and product stakeholders.
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Trained annotators label bounding boxes, masks, tracks, transcripts, or 3D cuboids in your toolchain or our workspace.
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Multi-pass review, consensus scoring, and automated checks before any dataset reaches your training jobs.
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Receive COCO, JSON, Pascal VOC, or custom exports — plus ongoing support as your models and taxonomies evolve.
Answers about scope, quality, tooling, and delivery.
Bounding boxes, polygons, keypoints, semantic and instance segmentation, OCR boxes, and custom taxonomy labels for any computer vision model.
Written guidelines, consensus review, inter-annotator agreement checks, and multi-pass QA before datasets reach your training pipeline.
COCO JSON, Pascal VOC, YOLO, custom schemas, and direct integration with your MLOps or cloud storage workflows.
Talk to our enterprise team about volume, timeline, QA targets, and pricing.