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Data annotation is the labelling of images, video, text and audio so machine learning models have something to learn from. We provide managed annotation teams with defined quality guarantees, multi-pass review and agreement scoring, because model accuracy is bounded by label accuracy.
High-quality labeled data — the fuel that makes your AI models accurate and reliable.
Bounding box, polygon, and keypoint annotation
Semantic segmentation and instance labeling
Text classification, NER, and intent tagging
Multi-stage quality assurance workflows
Autonomous vehicle and ADAS training data
Medical imaging and radiology datasets
Document AI and OCR model training
Object detection for retail and security
Every batch goes through multi-pass review with a defined agreement threshold between annotators, and disagreements escalate to a domain reviewer rather than being averaged away. We report inter-annotator agreement per batch, so you can see the label quality your model is actually being trained on.
Images and video, covering bounding boxes, polygons, segmentation masks and keypoints, plus text classification, named entity tagging, and audio transcription and labelling. Domain-specific work such as medical or document annotation is handled with reviewers trained for that domain.
Annotation runs under NDA on access-controlled infrastructure with no local downloads, and where required, entirely within your own environment so data never reaches ours. For personal data we can apply pseudonymisation before annotation begins.
Tell us about your project and we'll put together a tailored approach.
Book a Free ConsultationFrom a first conversation to a production deployment — we work alongside your team to build AI solutions that create measurable ROI from day one.