Computer vision annotation
Bounding boxes, polygons, image segmentation, keypoints and classification for images and video frames.
Data Annotation & Labeling
Data annotation and labeling with human judgment built in
Labels are only as good as the guidelines and reviewers behind them. One6 annotates image, video, text and audio data with trained contributors, written guidelines agreed with your team, and review steps that catch disagreement before it reaches your training set.
What we deliver
Text labeling
Classification, entity tagging, intent and sentiment labeling, and content categorization for NLP and LLM pipelines.
Audio annotation
Transcription, speaker labeling, timestamps and sound-event tagging for speech and audio models.
Guideline design and QA
We help turn your label taxonomy into clear instructions, then measure agreement and review samples throughout the project.
Common use cases
- Labeling perception data for computer vision models
- Categorizing and tagging text for classifiers and search
- Transcribing and segmenting audio for speech models
- Re-labeling or auditing an existing dataset with quality problems
How a project works
- 01
Scope
A short call to understand your model, data requirements, quality bar and timeline.
- 02
Pilot
A small first batch so you can review real output before committing to volume.
- 03
Scale
Once the pilot meets the agreed bar, we staff up and deliver in regular batches with ongoing QA.
Frequently asked questions
Do you work in our annotation tool or yours?
Either. We can work inside the platform your team already uses or propose tooling during scoping. The choice is confirmed before the pilot.
How is annotation quality measured?
Quality checks are agreed upfront and typically combine gold-standard examples, reviewer sampling and agreement between annotators. You see the results during the pilot.
Can you handle specialized domains?
Yes. For technical material we staff domain experts rather than general annotators — see expert human evaluation.
Related services
- Human Evaluation for AI ModelsDomain experts and trained generalists rate, test and review model output.
- AI Training Data CollectionVoice, text, image, video and custom datasets collected from real people to your specification.
- Multilingual AI DataNative-speaker collection, transcription, localization and evaluation across languages.
Planning a data annotation project?
Tell us what your model needs. We'll come back with questions, a proposed approach and a pilot plan.