Translation & Post-Editing
Human translation with MT post-editing support. Native speakers for each locale. Style guides enforced. Legal, medical and technical registers handled.
Human-led translation, transcription, NER, classification and cultural adaptation across 100+ languages — with structured quality assurance built in from day one.
Six core capabilities span the full multilingual data stack — from raw transcript to production-ready training data. Every step is handled by vetted native speakers under a governed quality framework.
Human translation with MT post-editing support. Native speakers for each locale. Style guides enforced. Legal, medical and technical registers handled.
Audio-to-text transcription with timestamping, speaker diarization and dialect tagging. Ideal for ASR model training datasets.
Multi-language NER annotation: people, organisations, locations, dates and custom entity types. Spans labelled with schema consistency checks.
Sentiment, intent, topic and toxicity classification. Multi-label schemas supported. Ambiguity resolved by consensus protocols, not single annotators.
Beyond translation: idioms, humour, tone and cultural sensitivity reviewed by in-country specialists. Avoids literal translation failures.
Dedicated QA reviewers separate from annotators. Inter-annotator agreement tracked. Rework loops with root-cause logging. Audit trail per batch.
Multilingual programs run through a five-stage pipeline — from task design to verified output. No ad-hoc crowdsourcing at any step.
Language pairs, volume, domain and quality bar defined. Talent pool matched to locale and subject matter.
Pre-validated speakers activated. Language test sample completed before full assignment.
Annotators work within a structured tooling environment. Throughput monitored in real time.
Independent QA layer reviews samples. Errors categorised, root-caused and fed back.
Verified output with quality metrics and audit trail. Rework SLA included as standard.
Most multilingual data vendors offer either cost efficiency or quality control but rarely both. Fuzu Atlas operates from a 3M+ talent pool with genuine geographic spread, so rare language pairs and regional dialects are accessible without synthetic workarounds.
Governance is the operating model, not an add-on. Every workflow includes QA authority, audit logging and error taxonomy from the start.
Pricing fits both growth-stage AI teams and global enterprises — enterprise-grade delivery without enterprise-grade procurement overhead.
Start with a focused PoC — defined scope, clear quality targets and a working output in weeks.