mSUBS combines frame-accurate AI captioning with human-in-the-loop linguistic QA — the only stack that meets both broadcaster turnaround and regulator-grade accuracy.
Illustrative · Linguist edit pass is the moat
The difference between "AI-generated subtitles" and broadcast-grade subtitles is the operating layer around the model.
Domain-adapted ASR for news, sports, drama, factual. Speaker diarization. Code-mixed Indic & Levantine Arabic. Sound-effect tagging for SDH.
Termbase + style-guide grounded translation. Cultural register selection. Right-to-left layout. CPS-aware segmentation for caption-card constraints.
Our network of 2,400+ vetted linguists reviews high-stakes content. Two-pass QA for regulator-facing material. Audit trail per line.
Drop a file. Pick languages. Set QA tier. The system handles the rest.
Drop video, audio, or script. Auto-detect language & format.
Frame-accurate ASR. Speaker diarization. SDH tagging.
Per-language pipelines. Termbase, glossary, style guide.
Vetted linguist QA. Two-pass for high-stakes content.
SRT · VTT · TTML · burn-in. Per-platform spec.
Every spec the workflow needs to drop into a real broadcast or streaming operation.
| Output formats | SRT · VTT · TTML · iTT · STLPlus burn-in render at any resolution. |
|---|---|
| Languages | 38 in production · 70+ on roadmapIncluding Indic vernaculars and Gulf Arabic. |
| Turnaround | 2-hour SLA · per episodeLower with reserved capacity. |
| Compliance | FCC · CRTC · CAP · DPPBroadcaster compliance built in. |
| QA tiers | AI · Linguist · Two-passPick the tier per project. |
| Integrations | MAM · Aspera · Frame.io · S3Watch-folder or API ingest. |
Send us a 5-minute clip. We'll return it captioned in three languages, with linguist QA, by tomorrow morning.