Language models & NLP
Clean entity, intent and classification labels are the difference between a model that understands and one that guesses. We review every batch for taxonomy consistency.
Sector · Language
Annotation for text, voice & documents.
Language models and voice AI need structured, consistent ground truth. We label the text, audio and documents that teach models to understand entities, intent, sentiment — and who said what.
What we label
What we annotate.
Named-entity recognition
Intent & sentiment
Text classification
Relation extraction
Document layout & OCR review
Transcription
Speaker diarization
PII redaction
Where it's used
How it's used.
Voice & speech AI
Transcription, diarization and intent tagging feed voice assistants, call-analytics and speech models — capturing who spoke, what they meant, and what happened.
Document intelligence
Layout, field and OCR-correction labelling turns messy documents into structured training data for document-AI pipelines.
Multilingual-capable and growing — a good fit for teams building LLM, chatbot, voice-assistant or document-AI products who need a review-driven labelling partner.
