AI models learn from labeled examples. We make sure those examples are right, and that the people creating them are trained, fairly paid and growing in their careers.
We started as a small team of annotators who saw two problems in the industry: clients receiving inconsistent data, and labelers doing careful work without training, feedback or a path forward.
So we built a company around both. Every labeler is trained and certified before touching client data, gets feedback on every reviewed batch, and can move up from annotator to QA reviewer to project lead.
Today we work with AI teams in Europe, North America and Africa on computer vision, language and speech projects.
Supported by in-house QA reviewers and project leads.
AI startups, research labs and enterprise ML teams.
Plus several regional languages.
We'd rather renegotiate a deadline than deliver data that quietly hurts your model.
Transparent pay rates above the local living wage, paid weekly, with no hidden deductions.
Paid training, certifications and a clear path into QA and project leadership.
Access controls, NDAs and wellbeing support for anyone reviewing sensitive content.
Many annotation projects require specialized knowledge. We provide project-specific training, guidelines, practice tasks, assessments and feedback to help qualified candidates understand the work before entering production.
Learn the specific annotation guidelines and workflow.
Work through examples before production.
Understand mistakes and improve accuracy.
Build experience across data types and AI workflows.
Move into reviewer, QA, team-lead and operations roles.
