Industries
Seven sectors. One approach.
Annotation is never sector-neutral. Below is where our labelling experience is genuine — the vocabularies, sensitivities and accuracy bars we've actually delivered against.
Sector by sector
Same discipline. Different contexts.
A clinical transcript needs one kind of care — a financial contract another, a product-catalogue image another still. The annotation console underneath is shared; the guidelines, taxonomies and review bar are tuned per sector.
Healthcare & Life Sciences
De-identified clinical-text annotation, medical-imaging labelling and trial-record classification — with the sensitivity handling clinical data demands.
Financial Services
Transaction tagging, KYC document labelling and risk-signal annotation — where every label has to hold up under audit, not just under a demo.
Technology
LLM training data, prompt/response evaluation, preference labelling and telemetry annotation for teams shipping real ML into production.
Retail & E-commerce
Product-catalogue attribute tagging, review-sentiment labelling and image classification that keeps merchandising, search and recommendation honest.
Education
Content classification, assessment-item tagging and learning-signal review for institutions, publishers and edtech ML teams.
Professional Services
Contract & clause annotation, document redaction and knowledge-base tagging — confidential work, structured properly.
Public Sector
Record classification, form-field extraction and citizen-data annotation with the discipline that public work demands.