Built for accountable work
LabelQuill is a platform for remote AI data annotation work: training people, checking their work and keeping a record of every decision. Capabilities open as their operational and legal prerequisites are met.
A development preview, said plainly
There is no registered company, live hiring programme, customer roster, payout provider or verified earnings programme today.
Those facts are constraints on the product, not details to hide. Any launch decision has to update this site and its legal pages before it reaches applicants.
Where it stands
What works in the preview, and what does not exist yet.
Working in the preview
- Accounts and applications
- Registration, a five-section application with drafts, and administrator review.
- Training and qualification
- Four training modules and the General Qualification, scored automatically.
- Practice marketplace
- Synthetic tasks with automatic checks, reviewer decisions and a simulated ledger.
Not in place yet
- Client projects
- No customers, no production task inventory and no paid work.
- Providers
- No production identity verification and no payout provider.
- Operating entity
- No registered company or live hiring programme sits behind the site.
What we hold to
- Clarity before conversion
- Applicants should know the platform’s stage, process and limits before they share any information.
- Rules applied consistently
- Eligibility, reviews and financial events are decided by server-side rules, not by what a page shows.
- Sensitive data earns scrutiny
- Identity and payout data belong with qualified providers and minimal retention, not improvised workflows.
- Operations before scale
- Auditable administration, support and quality review come before inviting more people in.