Vernacular AI Data Services
End-to-end pipelines that turn raw South Indian language voice and text into structured, validated, model-ready datasets — across six core service lines.
Data Annotation
High-quality localized labeling of text, image, audio, and video to build structured supervised-learning sets. Entity tagging, intent classification, bounding boxes, segmentation, and audio event labels — all reviewed by native speakers.
Best for: training data for NER, intent models, computer vision, and multimodal LLMs.
Speech Collection
Field and studio recording from native populations across regional dialects, accents, age groups, and emotional tones. Scripted prompts, spontaneous speech, and conversational data with rich speaker metadata.
Best for: ASR/TTS training, speaker ID, and emotion recognition.
Indic Transcription
ASR-ready verbatim transcripts with precise phonetic markers, local spelling conventions, timestamps, and speaker diarization. Code-switching (Tanglish/Tenglish) handled natively.
Best for: speech-to-text benchmarking and ASR fine-tuning.
Translation & Transcreation
Bridging local terminology with English while preserving cultural intent. Parallel corpora, domain glossaries, and transcreation for marketing, legal, and conversational content.
Best for: NMT systems and localized product experiences.
RLHF & LLM Evaluation
Annotator-driven human preference alignment (RLHF), red-teaming, safety checks, and factual validation tuned for Indic cultural context and language nuance.
Best for: aligning and evaluating multilingual LLMs.
Data QA & Validation
Rigorous multi-level evaluation — guideline creation, annotator qualification, dual review, adjudication, and final sign-off — to guarantee consistency and accuracy at scale.
Best for: enterprise programs that demand measurable quality SLAs.
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