Precision Annotation
Our proprietary DGX-BAD standard enforces systematic multi-pass verification on low-resource dialect outputs. Native speaker verification guarantees cultural authenticity and prevents hallucinated tokens, ensuring data purity for critical AI applications.
Each dataset undergoes rigorous, human-in-the-loop oversight. Our specialized Kurdish linguistic experts meticulously review and validate every data point, aligning with the exact tolerances required by foundational models.
Our Core Mandate
Eliminating low-resource language noise in AI training pipelines.
We are committed to providing the clean, verified data essential for robust LLM performance in Bahdini and Sorani.
Request DGX-BAD Protocol Documentation
Access comprehensive technical specifications and compliance sheets for our quality control framework.