Service practice
Data For AI & Training
Human-reviewed data operations that help AI teams build, evaluate, and improve models with reliable, well-governed training and validation data.
Give AI systems the structured data and feedback they need.
Annotation and labeling
Prepare text, image, audio, video, and document datasets with consistent guidelines and quality checks.
Model evaluation
Review outputs for accuracy, safety, usefulness, tone, and policy alignment using trained human evaluators.
AI operations
Maintain human-in-the-loop workflows for data collection, moderation, red teaming, and continuous model improvement.
Child services
Text and document labeling
Classify, extract, summarize, and structure business and domain-specific content.
Computer vision annotation
Bounding boxes, segmentation, key points, image classification, and video tagging.
RLHF and response ranking
Compare and rate model outputs using rubrics designed for target use cases.
Data quality management
Sampling, audits, adjudication, guideline refinement, and reviewer calibration.