High-quality data, collected right.
Consent-aware pipelines to source, label, and audit text, speech, images, and video at scale. Gold sets, IAA, and multi-pass QC keep labels consistent.
Raw Data
Text / Image / Audio
Model Ready
Training Datasets
Comprehensive coverage.
Text & NLP
Prompts, intents, entities, sentiment analysis, and safety labeling.
Computer Vision
Images (people, objects), video segments, and keypoint annotation.
Speech & Audio
Read & spontaneous speech, speaker diarization, and transcription.
Documents (OCR)
Scans, forms, receipts, and table extraction.
Supported Tasks
Rigorous Governance.
A multi-layered defense against data drift.
Gold sets & spot checks
IAA metrics
Error taxonomy
Gold sets & spot checks
Calibrated intervals ensure consistency and accuracy throughout the annotation process with regular quality validation.
IAA metrics
Cohen's κ / Krippendorff's α and reviewer feedback loops to measure inter-annotator agreement and improve label quality.
Error taxonomy
Accuracy, span, class, policy errors tracked with pass thresholds set collaboratively to maintain quality standards.
Drift & bias dashboards
Live counters across languages, regions, and demographics to monitor and prevent dataset bias in real-time.
Privacy compliance
Consent artifacts linked to file IDs, PII minimization, revocation window, encrypted transfer & role-based access.
Integrated with