Human intelligence, inside your data.
Vetted domain experts, embedded in your workflow. Specialists work inside yourstandard — not a crowd’s — driven by clear guidelines, with disputed samples reviewed independently and calibrated against measured agreement. Engagements run project-based, long-term, or embedded on-site. This layer underwrites the quality of every other data category we build.
Domain-native experts, matched to your data.
Experts are matched from a rigorously vetted pool spanning annotation, data engineering, and model evaluation — chosen for the domain your data lives in.
Talent Service
Vetted specialists who work inside your team and to your standard.
- Proven expertise
Rigorously vetted specialists with real project experience — not an anonymous crowd.
- Enterprise-ready
Accustomed to enterprise-grade standards, tooling, and delivery workflows.
- Flexible engagement
Project-based, long-term, or embedded on-site — matched to how you actually work.
- Seamless integration
Experts operate inside your standard and guidelines, not a generic labeling brief.
Expert Annotation & Review
A calibrated pipeline where quality is measured, not asserted.
- Multimodal & bilingual labeling
Image, video, text, audio, and sensor data annotated across English and Chinese.
- Independent dispute review
Disagreements route to an independent reviewer; the rationale is captured, not overwritten.
- Standard unification
Recurring disputes feed back into the guidelines so ambiguous cases resolve consistently.
- Quantified agreement
Inter-rater agreement is measured on sampled items and reportable to you.
Across every modality.
Throughput scales with the complexity of the data and the precision of the spec — never at the expense of the standard.
A precision-engineered annotation workflow.
Guideline design
Explicit decision criteria are written first, so specialists converge before any labeling begins.
Expert vetting & matching
Specialists are matched to your domain from a vetted pool spanning annotation, data engineering, and model evaluation.
Multimodal, bilingual annotation
Image, video, text, audio, and sensor data labeled across languages, with a full expert record kept.
Independent dispute review
Disagreements are routed to an independent reviewer; the reasoning is recorded rather than silently resolved.
Standard unification
Recurring disputes feed back into the guidelines so the next ambiguous case is already decided.
Agreement measurement
Inter-rater agreement is quantified on sampled items — quality as a measured statistic, not an assertion.
What ships
Human experts behind every breakthrough.
Tell us the standard your data has to meet, and we’ll embed the experts who can hold it — with agreement measured, not promised.