Representative scenarios across voice, annotation, RLHF and evaluation. Details are anonymized; the capabilities are real.
Challenge. A voice-AI company needed large volumes of consent-backed speech across several Indic and European languages, with tight quality and compliance requirements.
What we did. We ran the full pipeline — artist onboarding with explicit consent, managed recording, metadata tagging and QA — delivering accent-tuned, labelled audio.
Outcome. The team received a compliant, auditable dataset ready for ASR training, and scaled more languages on the same pay-on-approval terms.
Challenge. An enterprise fine-tuning a medical LLM needed qualified reviewers to judge accuracy and safety.
What we did. Our medical SME bench scored responses against a strict rubric and wrote reference answers, improving the signal in the preference data.
Outcome. Cleaner alignment data and defensible, expert-backed evaluation to support release decisions.
Challenge. A perception team needed consistent, high-accuracy labels across a large multi-sensor dataset.
What we did. We adapted tooling to their ontology and scaled 2D and 3D annotation behind gold-standard checks and four-stage review.
Outcome. Consistent labels at volume and a maintained post-QA accuracy bar, delivered on approved-only billing.
The same principles run through every engagement.
Explicit consent and auditable metadata on human and voice data.
STEM and domain SMEs on the tasks that need it.
Four-stage QA and gold-standard checks on every batch.
Pay only for the deliverables you approve.
Send us a sample task. You only pay for deliverables you approve.
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