Six services.
One quality bar.
Every workflow below is staffed by language-native AI Trainers, validated by AI cross-checks, reviewed by peers, and signed off by an expert QA Lead.
Indian Language RLHF
"Preference data that actually understands the user."
What it is
Native-speaker preference ranking, response evaluation and constitutional AI feedback across 22+ Indian languages — including code-mixed Hinglish, regional dialects and low-resource scripts.
Use cases
- Foundation-model alignment for Indic markets
- Preference pair construction for DPO / KTO
- Harm & refusal audits on sensitive topics
- Conversational assistant tone calibration
Languages supported
Pricing
Sample task
Hindi AI Training
"The most spoken language online. The most under-trained."
What it is
Purpose-built Hindi training data for LLMs — prompts, responses, cultural context, idiomatic usage, and code-mixed Hinglish at scale.
Use cases
- SFT datasets for Hindi-first or Hindi-primary models
- Devanagari + Roman Hindi script coverage
- Cultural references: festivals, cinema, regional foods, politics
- Domain expansion: agriculture, rural banking, healthcare
Languages supported
Pricing
Translation Evaluation
"Automated scores miss the meaning. Humans don't."
What it is
Human-in-the-loop quality scoring for Indic machine-translation models. BLEU and COMET are a floor — we provide the ceiling.
Use cases
- Per-sentence adequacy & fluency ratings
- Error typology (lexical, syntactic, semantic, cultural)
- MT regression detection on new checkpoints
- Golden test-sets for continuous evaluation
Languages supported
Pricing
AI Safety &
Red-teaming
"Safety is local. What's fine in SF breaks in Patna."
What it is
Adversarial evaluation of LLMs in an Indian context — political, communal, linguistic and cultural pressure tests that global red-team sets systematically miss.
Use cases
- India-specific harm taxonomies
- Jailbreak prompts across regional scripts
- Bias & representation audits (caste, gender, religion)
- Election & misinformation readiness
Pricing
Audio Annotation
"Accented, noisy, multilingual. Real India, transcribed."
What it is
Transcription, speaker diarization, emotion tagging and intent labeling for Indic audio — call-center streams, field recordings, broadcast media and on-device voice.
Use cases
- ASR ground-truth for low-resource languages
- Speaker attribution in multi-party conversations
- Emotion & sentiment tagging (7-class)
- Code-switching boundary annotation
Pricing
Expert Domain Tasks
"Where generalists fail, credentialed experts ship."
What it is
Domain-expert annotation and evaluation performed by verified specialists — licensed lawyers, qualified doctors, chartered accountants, CFAs and domain academics.
Use cases
- Legal case summarization & citation grounding
- Medical Q&A verification against Indian guidelines
- Financial / tax advice accuracy & compliance
- STEM reasoning with step-by-step checking