Multilingual AI Annotation
Native-speaker annotation in 50+ languages with cultural context, dialect awareness, and linguistic quality assurance — for AI that truly works globally.
AI Data in Every Language Your Users Speak
Building AI for global markets means training on data that represents the full diversity of human language. Centric Labs provides native-speaker annotation across 50+ languages — from high-resource languages like Mandarin and Spanish to low-resource languages like Pashto and Swahili. Our linguist-managed teams deliver cultural context and dialect precision that machine translation alone cannot achieve.
- 50+ languages with native-speaker annotators
- Dialect and regional variant differentiation
- Cultural localization beyond translation
- Linguistic QA with inter-annotator agreement metrics
- Code-switching and mixed-language handling
Multilingual Annotation Capabilities
Every language task — from NER to speech transcription — delivered by native speakers.
Text & NLP
NER, POS tagging, sentiment analysis, intent classification, and text categorization in any target language. Our linguists handle complex morphology, agglutinative structures, and scripts from Latin to Devanagari to CJK.
Speech & Audio
Transcription, segmentation, speaker identification, and pronunciation annotation across languages. We capture accent variations, dialectal differences, and prosodic features critical for ASR and TTS training.
Translation QA
Post-editing of machine translation, translation quality estimation, and parallel corpus creation. Our bilingual annotators evaluate fluency, adequacy, and terminology consistency across translation pairs.
Conversational AI
Dialog annotation, chatbot training data, and conversational flow labeling in local languages. We create natural, culturally appropriate conversations that reflect how real users interact with AI assistants in each market.
Content Moderation
Toxicity detection, hate speech classification, and content policy annotation in local languages. Native speakers catch the cultural context, slang, euphemisms, and coded language that automated systems miss.
Low-Resource Languages
Data collection, lexicon building, and annotation for underserved languages. We recruit and train native speakers for languages with limited existing NLP resources — from African languages to indigenous South Asian dialects.
Go Global With Multilingual AI Data
Tell us your target languages and use case — we'll match you with native-speaker teams and deliver a free pilot in your priority language.