Local AI Voice Systems
definition
A local AI voice system is a speech-to-text and text-to-speech stack that runs entirely on customer-owned hardware using open models like Whisper and Piper, so transcription and voice generation happen without sending audio to a cloud vendor or paying per-minute fees.
Voice and transcription are some of the most useful AI capabilities — and some of the most sensitive. Clinical notes, legal calls, internal meetings, customer recordings: sending that audio to a cloud vendor is a privacy and compliance problem, and per-minute billing punishes you for using it.
Most teams assume local voice is too slow or too hard to set up. It isn't anymore — but wiring it into a real workflow, on real hardware, reliably, is the part that takes engineering.
Stride deploys a private voice stack on your hardware: Whisper for high-accuracy transcription, Piper for natural text-to-speech, exposed through a clean API your other tools can call. No audio leaves the machine, no API keys, no per-minute meter.
We handle model selection, the deploy on your iron, and integration into the workflow that needs it — clinical notes, voicemail transcription, a field-service dictation tool — with a deploy session and a support window.
- ▸On-device clinical-notes transcription that replaced a per-minute cloud vendor
- ▸Voicemail-to-text for a maintenance line, running locally so tenant audio stays private
- ▸Field-service dictation that turns a technician's spoken note into a structured record
- ▸Text-to-speech for an operator tool, generated on-prem with tunable voices
Mic / audio file ──▶ Whisper (STT) ──▶ Text + structure
│
Your app / agent ◀───── REST / WebSocket ◀─────┘
│
▼
Text ──▶ Piper (TTS) ──▶ Audio out
[ everything runs inside your network — no cloud calls ]- ·No audio ever leaves your hardware; no third-party API keys.
- ·Ships as a Docker-compose service — deploys in well under an hour.
- ·Runs on commodity x86 and Apple Silicon; no GPU farm required.
Does any audio leave our machine?
No. The entire stack — speech-to-text and text-to-speech — runs on your hardware inside your network. There are no cloud API calls and no third-party keys, which is the whole point for privacy- and compliance-sensitive work.
What hardware do we need?
Commodity hardware is fine. It's tested on standard x86 machines and Apple Silicon — no GPU cluster required. We help you size it during the deploy.
How is this different from a cloud transcription API?
No per-minute billing, no vendor lock-in, and no audio leaving your environment. One client replaced a $480/month cloud transcription vendor with an on-device deploy in a single session.