Product pillar
Audio AI
Transcription, voice cloning, speech workflows and AI voice automation.
From transcription and dubbing to voice automation — reliable speech workflows without vendor lock-in.
Capabilities
- Speech-to-text (7+ providers)
- Real-time streaming transcription
- Speaker diarization and labelling
- Translation and dubbing pipelines
- Voice cloning (consent-gated)
- Text-to-speech routing (6+ providers)
- Voice-style transfer and emotion control
- Source separation (vocals / drums / stems)
- Speech enhancement and denoising
- Music generation and stems
- Sound-effect generation
- Sentiment and emotion detection
- Call audio ingestion and PII redaction
- IVR and voice-bot integration
- QC on WER, MOS proxies, silence
- Telephony / GDPR-aware deployment
- Batch archive processing
Use cases
Contact centers: summarize and route calls; assist agents with live suggestions.
Media: transcribe and subtitle large libraries.
Product: prototype voice UX before committing to hardware.
Compliance: redact PII in audio according to policy.
Process
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Capture requirements
Languages, accents, latency targets, compliance and retention.
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Prototype
Small audio sets to validate WER and UX before scale.
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Integrate
Hooks to your telephony or storage; least-privilege access.
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Operate
Monitoring, alerts and periodic model refresh planning.
Technology
Multi-provider STT/TTS with routing by language, cost and quality. For telephony, we design around jitter, codecs and regional regulations — scope compliance explicitly in the project.
Demo
A waveform + transcript mock is available on the demo page.
Quote
We work quote-only. Share your throughput, quality bar and deadlines — we respond with a scoped proposal.
Request a quoteFAQ
Do you offer real-time STT?
Yes where latency budgets allow; we validate on your audio profile.
What about phone audio quality?
We tune models and preprocessing for narrowband and noisy channels.
Is voice cloning allowed?
Only with clear rights and policy; we refuse ambiguous requests.
Can you work on-prem?
Depending on scope — ask early so architecture fits.
How do you handle GDPR?
Data minimization, retention limits and subprocessors are documented per deployment.