Image and video
Boxes, polygons, segmentation, keypoints and tracking.
Vision, sensor, text and time-series
Data Annotation
Expert annotation across every modality a modern AI system consumes.
The Work Behind Every Working Model
Annotation is where a dataset either becomes an asset or becomes an expensive disappointment. The difference is rarely tooling — it is guideline quality, reviewer discipline and what happens when two annotators disagree.
What Is Included
3D and point cloud
Cuboids, semantic segmentation and multi-sensor fusion.
Text and documents
Entities, relations, classification and OCR correction.
Audio and speech
Transcription, diarisation and event labelling.
Time-series and telemetry
Event and anomaly annotation on sensor streams.
Multi-modal sets
Aligned annotation where several modalities describe one moment.
How We Work
- Guidelines before volume A pilot batch proves the guideline before anyone scales it.
- Trained, tested annotators People qualify on your task before touching production data.
- Layered review Annotate, review, audit — with the roles kept separate.
- Measured agreement Inter-annotator agreement is tracked and acted on, not just reported.
The Controls Behind It
- Gold-standard sets Held-out benchmarks measure quality continuously.
- Disagreement escalation Conflicts go to a senior reviewer instead of being averaged away.
- Versioned guidelines When a rule changes, it is dated and the affected data is identified.
- Full traceability Every label carries who, when and under which guideline version.
Ready When You Are
Tell us what you are building and we will come back with a plan, a sample and a price.