AI Training Data for Regional Languages
Most AI models don't work well in Turkish, Arabic, Persian, and Balkan languages because they lack quality training data. We provide human-validated datasets to train AI models that actually understand these languages.
Why AI Models Need Regional Training Data
Most AI models are trained mainly on English and Western European languages. When used in Turkish, Arabic, or Balkan markets, they struggle with:
Arabic Dialect Diversity
Gulf, Levantine, Egyptian, and Maghrebi dialects differ vastly from Modern Standard Arabic.
Balkan Language Gap
Serbian, Croatian, Bosnian lack quality datasets for hate speech detection and sentiment analysis.
Cultural Nuance
Idioms, humor, and cultural references are lost without native human validation.
We Solve This With:
The Technical Details, Up Front
What you get, how it's checked, and how fast it moves, before you ever get on a call.
Formats & Delivery
- Text: JSONL, CSV/TSV, XLIFF, or your custom schema
- Audio: WAV / FLAC, 16–48 kHz, with speaker & environment metadata
- Time-aligned transcripts: TextGrid, SRT, VTT
- RLHF: ranking / rating exports matched to your pipeline format
- Delivery via secure transfer, API, or your own platform
Quality Methodology
- Annotation guidelines co-developed with you, versioned per batch
- Calibration rounds before production starts
- Gold tasks seeded throughout; annotators tracked against them
- Inter-annotator agreement (IAA) measured and reported per delivery
- WER spot-checks on transcription; acceptance criteria agreed up front
Test us before you commit
Send us your spec and we'll deliver a free pilot batch of up to 100 annotated samples or 30 minutes of collected audio, with a QA report included. You evaluate the output against your own acceptance criteria. If it doesn't meet the bar, you've lost nothing.
Complete AI Data Services
From speech collection to human feedback, we provide the data your AI models need to work in regional languages.
Audio & Speech Data Collection
Native speaker recordings across accents, ages, genders, and acoustic environments. We cover under-resourced dialects and languages where off-the-shelf data simply doesn't exist.
Languages
Use Cases
RLHF & Human Feedback
Our linguists rank LLM responses, evaluate cultural appropriateness, and score factual accuracy to help your models become safer and more helpful in regional languages.
Languages
Use Cases
Content Moderation Data
Labeled datasets for hate speech, toxicity, misinformation, and sentiment. Our annotators understand cultural nuances, slang, and code-switching that automated systems miss.
Languages
Use Cases
Text & NLP Datasets
Parallel corpora, annotated text, and domain-specific datasets for machine translation, NER, and classification tasks in low-resource regional languages.
Languages
Use Cases
From Requirements to Deployment
Requirements Analysis
We analyze your AI model needs, target languages, and data specifications.
Crowd Mobilization
Our vetted 700+ linguist network provides native speakers for data collection.
Collection & Annotation
Multi-layered quality control ensures accurate, consistent, and clean datasets.
Validation & Delivery
Final human review and formatting, ready to drop into your pipeline.
Your Data Never Trains Public Models
The biggest concern for enterprise AI projects: data leakage. We guarantee complete isolation of your proprietary data with bank-grade security protocols.
End-to-End Encryption
All data transfers are encrypted in transit and at rest
ISO 27001
Information security management system
Isolated Environments
Dedicated processing environments per client
NDA Coverage
Strict NDA for every linguist and annotator
GDPR Compliant
Full compliance with EU and regional regulations
Audit Trails
Complete traceability for every data touchpoint
AI Models We've Helped Train
Representative projects. Client names withheld under NDA; references and sample deliverables available on request.
Global Tech Company
Challenge
Needed 50,000 hours of Turkish speech data across all dialects, ages, and acoustic environments for ASR training.
Solution
Mobilized 500+ native speakers across Turkey. Collected data in homes, cars, offices, and public spaces. Multi-tier quality validation.
Results
Social Media Platform
Challenge
Struggling with hate speech detection in Arabic dialects. Generic models trained on MSA were failing on Gulf, Levantine, and Egyptian Arabic.
Solution
Created custom hate speech and toxicity dataset with 100K+ labeled examples across 5 Arabic dialects. Native annotators with cultural context.
Results
Enterprise AI Startup
Challenge
Building a Turkish-language LLM but lacked quality RLHF data for instruction tuning and alignment.
Solution
Provided 50+ expert annotators for RLHF tasks: response ranking, quality scoring, prompt evaluation. Domain-specific feedback for business, legal, medical.
Results
Ready to Train Your AI With Quality Regional Data?
Let's discuss your AI project requirements and how our multilingual data services can help.