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Language built in. Not bolted on.
Every Qorden product runs on a single shared language engine. The same translation, transcription, and voice AI works underneath all of them. Consistent, fast, and always improving.
How QDub works.
One engine
Every product draws from the same language core. Meetings, dubbing, voice translation, and speech analytics all run on it. No fragmentation across the suite.
One standard
Accuracy, speed, and language support are the same everywhere. What works in Qordenate works exactly the same way in QSAP.
One roadmap
Every improvement to the language engine reaches every product at the same time. No separate per-product updates. No waiting
One layer powering every language experience
Just like your phone runs every app on a single operating system, Qorden runs every product on one shared language engine. A unified foundation beneath everything—so every feature, workflow, and tool builds on the same core.
Real-time translation, transcription, voice processing, and analytics work as one—no silos, no duplication. Updates in one place improve everything, keeping quality consistent.
Qorden Product Suite
- Live meetings
- Voice translation
- Video dubbing
- Speech analytics
Foundation
- Real-time translation
- Transcription
- Speaker identification
- Voice cloning
- Language detection
- Sentiment analysis
- Multilingual Summarization
Four products. One language core.
Live multilingual meetings
Real-time translation and transcription for video calls. Every participant hears the meeting in their own language as it happens.
Real-time voice translation
Translate spoken audio into another language as it happens. Works for calls, live streams, broadcasts, and any live audio feed.
AI video dubbing
Localise recorded video into multiple languages with lip-sync AI dubbing. Built for content creators, studios, and media teams.
Contact centre speech analytics
Analyse customer conversations across languages to surface insights, compliance signals, and service quality data automatically.
How QDub works.
Qorden Language OS
Context-aware accuracy
Meeting speech, dubbed audio, and contact centre calls each use models tuned for that context. Not a generic engine applied to everything.
Low latency by design
The language layer sits inside the product. Speed is structural, not something fixed after the fact.
Every product improves together
A better translation model means better meetings, better dubbing, and better analytics. All at once.
Translation as a feature
One model for everything
The same translation API that handles emails handles live speech. No context awareness. Inconsistent results across the platform.
Latency added at every step
Every translation is a separate round trip. In live audio this is noticeable. In real-time meetings it breaks the experience.
Updates are per product
Improving language in one area does not improve the rest. Each product moves separately on its own timeline.