Language-agnostic by design
Track speakers across language switches and accent shifts without re-anchoring the model.
Editor-ready metadata, not raw output
Timestamps, speaker IDs, and confidence scores are formatted to drop directly into our media systems and dubbing orchestration tools.
Speaker continuity across full timelines
Match the same voice across an entire episode, season, or series. Casting decisions stay consistent automatically.
Use cases
Automated dubbing: Speaker-aligned scripts so each voice maps to one TTS
Subtitling & captions: Per-speaker labels for accessibility-grade captioning
Podcast & audiobook production: Speaker separation that preserves identity for natural multi-voice playback
Live broadcast & events: Low-latency diarization for real-time captioning and monitoring
Content indexing & search: Speaker-tagged archives, find every quote from any guest, instantly
Media monitoring: Search at scale across audio-visual archives by speaker, not just keyword
Features
Speaker diarization
Frame-accurate timestamps across long-form content
Speaker identification
Persistent identity across multiple sources.
Voiceprints
Searchable voice biometrics for archive indexing
Overlap detection
Handle interruption, simultaneous speech, and audience reactions
Confidence scoring
Surface which segments need a human, which don't
languages with consistent transcription
latency for live workflows
Hours of long-form
content processed for major platforms