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MULTILINGUAL AI DATA SERVICES

Multilingual Data Annotation for Smarter AI Models

High-quality training data procurement, multilingual annotation, and sentiment analysis services to power your LLMs and AI models across global markets.

  • Native annotators across 100+ languages
  • Secure data handling with NDA protection
  • Domain experts for specialized AI training data
  • Human-in-the-loop quality assurance
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Powering AI Models with Multilingual Data

From LLM training datasets to sentiment analysis, we provide the high-quality multilingual data your AI models need to succeed in global markets.

Multilingual Data Annotation
Text classification, NER, intent labeling, and POS tagging by native speakers across 100+ languages for AI/ML training.
AI Training Data Procurement
Custom dataset creation, LLM fine-tuning data, and domain-specific training corpora sourced and prepared to your specifications.
Sentiment & Emotion Analysis
Multilingual sentiment labeling, emotion classification, and opinion mining for training robust NLP models.

Why AI Teams Choose Laoret for Training Data

Building multilingual AI models requires more than raw data. It requires cultural context, linguistic accuracy, domain expertise, and rigorous quality control.

Native Multilingual Experts

Trained annotators who understand cultural nuances, idioms, and context across 100+ languages.

Domain-Specific Annotation
Subject-matter experts for specialized fields: medical, legal, financial, technical, and more.
Secure Data Processing
NDA-protected workflows, controlled access, and confidential handling of proprietary AI training data.
Human-in-the-Loop Quality
Multi-level validation, consistency checks, and expert review to ensure high-quality training data.

Comprehensive Data Annotation Services

Specialized annotation types to train AI models across languages, domains, and use cases.
Text Classification & Labeling
Category tagging, topic classification, content moderation labels, and custom taxonomy annotation for NLP models.
Sentiment & Emotion Analysis
Positive/negative/neutral sentiment, emotion classification, opinion mining, and aspect-based sentiment annotation.
Named Entity Recognition (NER)
Person, organization, location, date, product, and custom entity tagging in multilingual text for information extraction.
Intent & Dialogue Annotation
Conversational AI training, chatbot intent labeling, slot filling, and dialogue flow annotation for virtual assistants.
Translation Quality Assessment

Human evaluation of machine translation output, fluency scoring, adequacy rating, and error annotation for MT improvement.

Audio Transcription & Annotation
Speech-to-text transcription, speaker diarization, emotion labeling, and audio event tagging for voice AI models.
Image & Video Annotation

Object detection, semantic segmentation, bounding boxes, and multilingual caption annotation for computer vision models.

Custom Dataset Creation

Domain-specific corpus building, synthetic data generation, data augmentation, and LLM fine-tuning dataset preparation.

Quality-Controlled Annotation Workflow

From data intake to final delivery, every annotation cycle includes training, validation, and quality assurance.

1

Data Intake & Scope

Dataset review, annotation guidelines, language pairs, and project requirements are defined.

2

Annotator Training

Native experts are onboarded with custom guidelines, examples, and domain-specific context.

3

Annotation & Labeling

Data is annotated through secure platforms with quality controls and consistency tracking.

4

Multi-Level QA

Expert review, inter-annotator agreement checks, and validation cycles ensure high accuracy.

5

Delivery & Iteration

Final datasets are delivered in your format with optional feedback loops for refinement.

AI & Machine Learning Use Cases

  • LLM fine-tuning for multilingual markets
  • Chatbot & virtual assistant training data
  • Sentiment analysis model development
  • Content moderation AI training
  • Voice assistant & speech recognition data
  • Machine translation quality evaluation
  • Multilingual search & recommendation systems
  • Domain-specific NLP model training (medical, legal, financial)

Quality, Accuracy, and Data Security at Every Step

ISO-Aligned Quality
NDA-Ready Workflows
Human Expert Review
Secure File Handling
Trusted for high-quality multilingual training data across AI/ML applications and global markets.
Building Multilingual AI? Let's Talk Training Data.

Whether you’re training LLMs, developing sentiment analysis models, or building conversational AI, we provide the high-quality multilingual datasets you need to succeed.

  • Fast turnaround on samples
  • NDA-protected data handling
  • Quality metrics & validation
Discuss Your AI Project
Request Sample Dataset

Request AI Training Data

Share your AI project requirements and our team will review your training data needs confidentially. This form is designed for ML teams, AI companies, and organizations building multilingual models.

  • Confidential data review
  • Custom dataset proposals
  • Sample annotation available
  • Dedicated AI data specialist response
  • Request Training Data
Your information will be handled confidentially and used only to respond to your request.