Transcription and video labels for audio-first AI.
Voice agents, media models and video understanding all need clean human ground truth. Labelix runs dedicated, in-office pods for transcription, speaker and event labeling, and frame-level video annotation — including multilingual work.
- Independent & neutral
- In-office · NDA-bound
- Live in ~3 weeks
- Never crowdsourced
The annotation your models actually need.
The bottleneck isn't the model. It's the labels behind it.
Transcription and tagging must stay consistent across accents, domains and languages.
New languages or domains need fresh labeled audio — fast — to keep models sharp.
Audio and video can be sensitive; they belong in a controlled environment, not a gig pool.
A dedicated team — not a crowd you can't see.
Voice agents & call analytics · media & music AI · video understanding · multilingual speech data.
A dedicated pod, live in ~3 weeks
We recruit and train a dedicated, in-office team for your domain and ramp it under daily QA — not a rotating, anonymous crowd. A small paid pilot proves quality before you scale.
Independent & data-firewalled
No Big-Tech owner, no conflicted incumbent. Your data is handled by vetted staff under signed NDAs in a controlled, access-controlled environment — never farmed out.
Consistency that compounds
The same retained team learns your taxonomy and edge cases, so each new product line, region, template or language is a re-train — not a restart.
Questions, answered straight.
Still have one? Tell us about your data and we'll scope a small paid pilot.
Audio and video annotation is the human labeling of sound and footage — transcription, speaker and event tagging, and frame-level object and action labeling — so voice and video AI have clean ground truth. Labelix does this, including multilingual work, with a dedicated, in-office team.
Audio transcription, speaker labeling and diarization, event/sound tagging, voice sentiment and intent, and frame-level video object and action labeling — including multilingual projects, scoped to your guidelines.
Yes. We recruit native-language annotators into your dedicated pod, so multilingual transcription and tagging is handled by people who actually speak the language — not machine-only pipelines.
Detailed guidelines, calibration sessions and layered QA on a retained team. Because the same annotators stay on your project, accuracy on domain terms and accents improves over time rather than resetting.
Yes — work happens with vetted staff in an access-controlled facility under NDA, within a controlled environment. We don't distribute sensitive media to anonymous crowd workers; your data and outputs remain yours.
Put a dedicated speech · audio · video pod on your data.
Start with a small paid pilot — see the quality before you scale. Independent, in-office, and live in about three weeks.