Every service runs on the same foundation: labelers certified on your guidelines, two-stage review and transparent quality reporting.
For object detection, segmentation and classification models.
For tracking, activity recognition and autonomous systems.
For search, support automation and language models.
For speech recognition, call analytics and conversational systems.
For teams training and testing language models.
For OCR, extraction and finance workflows.
High-precision 3D labeling for autonomous vehicles, robotics, mapping and perception.
Visual annotation for models that need to detect, recognize, locate and understand objects and scenes.
Pixel-precise annotation that helps models distinguish objects, regions and scene elements.
Use machine-generated labels as a starting point, with humans validating and correcting the final output.
Every batch is labeled, then reviewed by a senior QA reviewer, then spot-checked by a project lead before delivery. Items that fail go back to the original labeler with written feedback.
Per item, per hour or per dedicated team, depending on task complexity.
No minimum for pilots. Production projects are scoped around volume and workflow.
Agreed per batch, typically 24–72 hours for standard production work.
Our platform or yours — we work in common labeling tools and client environments.
Review the dataset, taxonomy, annotation guidelines and acceptance criteria.
Prepare and qualify annotators around the project workflow.
Produce labels using your preferred tools and project standards.
Identify inconsistencies, return failed items and incorporate feedback.
Send a sample and your guidelines. We will help scope a practical pilot and production workflow.
Request a pilot →