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Share Your Data
Upload raw images, video, text, audio, or LiDAR securely — we ingest from cloud storage, SFTP, or your existing ML pipeline.
Annotation service
Annotation Quality Assurance
Multi-tier annotation QA — golden sets, IAA measurement, auditor consensus, and continuous dataset validation for enterprise ML.
- Golden set benchmarking
- Inter-annotator agreement tracking
- Auditor consensus workflows
- Weekly quality reporting
Service overview
Annotation QA is not a final checkbox — it is an operational system. Our quality assurance services combine golden sets, inter-annotator agreement measurement, auditor consensus, and production error mining so datasets stay aligned with model performance targets.
Golden sets and acceptance thresholds
Curated difficult examples with adjudicated labels become the benchmark every batch must pass before export.
IAA and error taxonomy
Agreement tracked by class, capture condition, and annotator cohort — with root-cause tagging that drives guideline improvements.
Continuous validation loops
Re-audit after taxonomy changes, validate auto-label outputs, and refresh datasets when production drift appears.
Reporting for ML and compliance stakeholders
Weekly dashboards, release gate summaries, and audit trails compliance teams can review.
QA as a managed service
Standalone QA on your labels or embedded QA within full annotation programs with shared PM accountability.
Get started
Strengthen QA before your next model release. Share current accuracy gaps and taxonomy — we propose QA tiers, sampling rates, and reporting cadence.
Industries we serve
Our annotation process
A proven calibration-to-production workflow for enterprise annotation programs.
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Project Analysis
We define labeling guidelines, class taxonomy, edge cases, and accuracy targets with your ML and product stakeholders.
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Annotation
Trained annotators label bounding boxes, masks, tracks, transcripts, or 3D cuboids in your toolchain or our workspace.
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Quality Assurance
Multi-pass review, consensus scoring, and automated checks before any dataset reaches your training jobs.
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Delivery & Support
Receive COCO, JSON, Pascal VOC, or custom exports — plus ongoing support as your models and taxonomies evolve.
Service FAQ
Answers about scope, quality, tooling, and delivery.
Annotator pass, senior review, and auditor sign-off with documented disagreement resolution and error categorization.
Yes. We audit vendor deliverables, fix systematic errors, and re-benchmark against your production metrics.
We compute agreement on overlapping samples, stratify by class difficulty, and feed results into guideline updates.
Ready to start your annotation quality assurance project?
Talk to our enterprise team about volume, timeline, QA targets, and pricing.