Industry solutions · computer vision data annotation services
Computer vision
Image and video data collection, bounding boxes, segmentation, tracking and QA for detection, safety, inspection and visual intelligence models.
Industry reality
Data quality depends on the failure modes of computer vision.
A useful dataset must represent how the product will actually be used—not just reach a large row count. We design the workflow around domain constraints, model risk and measurable acceptance.
Discuss your use case ↗Common challenges
What makes this data difficult.
Inconsistent geometry and class boundaries
Temporal labeling errors in video
Device, lighting and geography bias
High-value use cases
Programs designed around product outcomes.
01
Object detection and classification
02
Semantic and instance segmentation
03
Video tracking and event labeling
04
Visual quality inspection
05
Safety and compliance monitoring
Typical deliverables
More than a folder of files.
The exact specification is project-dependent, but delivery should make provenance, quality, format and limitations understandable.
Collection and coverage specification01
COCO, YOLO, MOT or custom exports02
Audited geometry and class labels03
Temporal consistency checks04
Dataset card and error taxonomy05
Recommended capabilities
Build the operating model around the use case.
01Source
Custom data collection
Consent-aware collection programs designed around your target population, environment, modality and model objective.
Explore service ↗02LabelData annotation
Human annotation workflows with clear taxonomies, calibrated reviewers and measurable acceptance criteria.
Explore service ↗03VerifyDataset QA
Independent audits for label quality, leakage, imbalance, duplication, provenance and documentation quality.
Explore service ↗Frequently asked questions
Questions about computer vision data.
Which computer-vision annotations are supported?+
Projects can include classification, boxes, polygons, masks, keypoints, tracks, OCR regions and event-level video labels.
Can you collect images as well as annotate them?+
Yes. Collection and annotation can be combined when existing data does not represent the production environment.
Build for the real environment
Plan a computer vision data program.
Tell us the model objective, current failure mode and available data. We will help structure the pilot and acceptance criteria.
Start a conversation ↗