Data Annotation

What this service does

AI models are only as good as the data they learn from. Data annotation is the careful, human work of labelling that data — marking what is in an image, what a sentence means, where a sound starts, or whether an answer is correct — so a model can learn the right pattern instead of a noisy one.

The expert tier is the difference. General labelling is a commodity; expert-reviewed annotation, with clear guidelines, second review and measured accuracy, is what teams building serious models actually need. Every batch is checked, disagreements are resolved by a reviewer who knows the subject, and accuracy is reported — not assumed.

What’s included

• Text annotation — classification, entities, intent and sentiment
• Image and video annotation — boxes, masks, keypoints and tracking
• Audio annotation — transcription, diarisation and event labelling
• Expert review and adjudication on disagreements and edge cases
• Guideline writing — clear, testable rules
• Quality reporting — accuracy, agreement rates and error patterns

Who it’s for

How we build it

A clear, low-risk path — you see the system working before you scale it.

What you receive

• Labelled data in your required format, with a documented guideline
• Expert-reviewed batches with a quality report per delivery
• An adjudication log showing how edge cases were resolved
• Guideline updates that make each batch more consistent

Frequently asked questions