Classification, NER, sentiment, and content moderation across 70+ languages — produced against your guidelines, with agreement measured and edge cases escalated rather than guessed.
Annotators, moderators, and QA reviewers for any project
Work inside any labeling platform or internal environment
Healthcare, finance, legal, and more across 70+ languages
One programme, run end to end, delivering accurate labels, consistent classifications, and production-ready datasets for your NLP models.
Our annotation team work inside any annotation tool or your internal environment. You control access and permissions. Your data never leaves your systems.
Built-in chat, document editor, and everything you need to coordinate annotation across distributed teams. Share guidelines and instructions, message your team, and keep everyone aligned in one place.
Pay our annotation team in any country from a single dashboard. You set the rates, we add a small fixed fee on top. No hidden costs, no chasing invoices.
We get a shortlist of qualified text annotators, content moderators, and QA reviewers ready to work in any labeling tool or internal platform. What we deliver:
Create your account, scope a project, and commission our annotation team who work inside your existing tooling.
Describe your project and the skills you need. Receive proposals from text annotators, content moderators, and QA reviewers with proven experience in your domain.
We agree the spec, then run delivery inside any annotation tool or your internal environment.
Share guidelines and taxonomies, message your team, and handle global payments from a single dashboard.
Send us a sample batch and we will come back with a spec and a quote.
A standing programme, run end to end, for continuous or large-volume work.
Send us your first batch and get text annotators, moderators, and QA specialists who work inside any annotation platform or your own internal systems.
The largest network of text annotators, linguists, and domain specialists, ready to work in any annotation platform or custom environment.
Quick answers to common questions about text annotation projects and annotation lead delivery on ReinforcedX.
The full range for text annotation: we scope the task types with you at kickoff, produce them against your schema, and QA every batch before it reaches you. If a task type is unusual, we pilot it on a small batch first so you can judge the output before committing volume.
Yes. Tell us the shape of the text annotation work and we will come back with a scope, a quality bar, and a price before anything starts.
Yes — tell us what you need for text annotation and we will scope it, agree the quality bar, and deliver against it. Every batch is reviewed before it reaches you.
We work inside whatever you already run — Label Studio, CVAT, V7, Argilla, Prodigy, or your own internal tooling. You control access and permissions, your data stays where it is, and the text annotation output lands in your system rather than ours.
Yes — tell us what you need for text annotation and we will scope it, agree the quality bar, and deliver against it. Every batch is reviewed before it reaches you.
A managed programme means we run the whole text annotation pipeline end to end — staffing, tooling, QA, and reporting — inside your environment. It is the right choice once volume is continuous or the work spans several teams, because you stop coordinating batches and start receiving them.
Deliver our annotation team on ReinforcedX, then invite them to any annotation platform or your own internal environment.
Three ways to work with us, from a single batch to a standing programme.
Send us the spec and we scope the work, agree the quality bar, and start delivering. We run inside the tools you already use, so output lands where your team works.
We staff, run, and QA the whole programme inside your tools. End-to-end operations for large or complex projects.
Keep a standing delivery pipeline running against your roadmap, with quality reported every week.
Typically within a week or two of a scope being agreed. The first delivery is deliberately a small batch so you can check the output against your expectations before volume ramps.
One process owner who knows the workflow, one engineer with access to the systems involved, and a weekly 45-minute review. No standing committee, and no requirement for an ML specialist on your side.
You do. Datasets, labels, weights, evaluation suites and runbooks are yours and are handed over at the end. Your data trains your models only, with zero-retention provider settings by default.
Yes, and the quality bar holds because the rubric and gold set are already agreed by that point. Ramping is a staffing question, not a re-scoping one, so it usually takes days rather than a new engagement.
Often you should not. The cases where teams move to us are when they cannot get a quality number out of their current vendor, or when the work is delivered as an opaque batch with no trace of how disagreements were resolved.
We stay on-call for 30 days at no extra cost, then move to an optional support retainer. Most teams also keep a quarterly evaluation review with us to catch drift early.
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