Translation & Post-Editing
Human translation with MT post-editing support. Native speakers for each locale. Style guides enforced. Legal, medical, and technical registers handled.
Core Solution
Multilingual Data
Operations
Human-powered translation, transcription, NER, classification, and cultural adaptation across 100+ languages — with structured quality assurance built in from day one.
100+
Languages covered
3M+
Native-speaker talent profiles
40+
Countries represented
Multi-layer
QA on every workflow
What We Deliver
The full multilingual data stack
From raw transcript to production-ready training data — every step handled by vetted native speakers under a governed quality framework.
Transcription & Speech Data
Audio-to-text transcription with timestamping, speaker diarization, and dialect tagging. Ideal for ASR model training datasets.
Named Entity Recognition
Multi-language NER annotation: people, organisations, locations, dates, and custom entity types. Spans labelled with schema consistency checks.
Text Classification
Sentiment, intent, topic, and toxicity classification. Multi-label schemas supported. Ambiguity resolved by consensus protocols, not single annotators.
Cultural Adaptation & Localisation
Beyond translation: idioms, humour, tone, and cultural sensitivity reviewed by in-country specialists. Avoids literal translation failures.
Quality Assurance Layer
Dedicated QA reviewers separate from annotators. Inter-annotator agreement tracked. Rework loops with root-cause logging. Audit trail per batch.
Delivery Model
How multilingual ops work at Fuzu Atlas
A structured pipeline from task design to verified output — no ad-hoc crowdsourcing.
01
Scoping
Language pairs, volume, domain, and quality bar defined. Talent pool matched to locale and subject matter.
02
Pool Activation
Pre-validated speakers activated. Language test sample completed before full assignment.
03
Production
Annotators work within a structured tooling environment. Throughput monitored in real time.
04
QA Review
Independent QA layer reviews samples. Errors categorised, root-caused, and fed back.
05
Delivery
Verified output with quality metrics and audit trail. Rework SLA included as standard.
Why Fuzu Atlas for Multilingual
Supply depth meets governance discipline
Most multilingual data vendors offer either cost efficiency or quality control — rarely both. Fuzu Atlas operates from a 3M+ talent pool with genuine geographic spread, meaning rare language pairs and regional dialects are accessible without synthetic workarounds.
Governance isn't an add-on — it's the operating model. Every workflow includes QA authority, audit logging, and error taxonomy from the start.
And we're priced to work for both growth-stage AI teams and global enterprises — enterprise-grade delivery without enterprise-grade procurement overhead.
Breadth
100+ languages, including low-resource
Swahili, Hausa, Amharic, Tagalog, and other underserved languages covered by genuine native speakers — not MT proxies.
Depth
Domain specialists, not general crowd
Medical, legal, financial, and technical content handled by pre-screened domain experts, not anonymous general annotators.
Trust
Full audit trail on every batch
Who annotated, who reviewed, when, and with what quality score — recorded per deliverable and available on request.
Ready to deploy multilingual intelligence?
Start with a focused PoC — defined scope, clear quality targets, and a working output in weeks.