Data Annotation & Labeling
High-quality training data for AI
Accurate, consistent labeled data for machine learning — image, video, text, and audio annotation, plus LLM evaluation and RLHF, with quality control built in.
What we do
Image & video annotation
Bounding boxes, polygons, segmentation, keypoints, and object tracking for computer vision.
Text & NLP labeling
Classification, named-entity recognition, sentiment, intent, and document extraction.
LLM evaluation & RLHF
Response ranking, preference data, red-teaming, and fact-checking to fine-tune and evaluate models.
Quality assurance
Clear guidelines, multi-pass review, and agreement metrics so every label is one you can trust.
How we work
- 1
Define
Agree on taxonomy, edge cases, and quality targets with a pilot batch.
- 2
Label
Annotate at scale with trained annotators and tooling matched to your data.
- 3
Verify
Review, measure agreement, and deliver clean datasets ready for training.
Typical deliverables
- Annotation guidelines & taxonomy
- Labeled datasets in your format
- Quality & agreement reports
- Scalable labeling workflow
Outcomes to expect
- Consistent, high-accuracy labels
- Faster model training cycles
- Datasets that scale with your roadmap
Tools & platforms
Ready to talk data annotation & labeling?
Tell us where you're headed — we'll come back with a plan, not a sales pitch.