Self-Hosted Voice AI
Build your own voice AI infrastructure. No vendor lock-in, full control over your data, and the ability to customize everything to your exact needs.
Why Self-Host?
Voice AI vendors charge per minute. At scale, those costs add up fast. Self-hosting gives you predictable costs, full control, and no dependency on a third party.
Cost Control
Per-minute pricing kills margins at scale. Self-hosting means predictable infrastructure costs that don't scale linearly with call volume.
- Predictable monthly costs
- Better unit economics at scale
- No surprise bills
Data Privacy
Your conversations stay on your servers. No third-party access to sensitive customer data. Full compliance control.
- Data never leaves your infrastructure
- HIPAA/SOC2 compliance ready
- Full audit trail control
Full Control
Customize everything. No waiting for vendor roadmaps. Build exactly what you need, when you need it.
- Custom model selection
- Integration flexibility
- No vendor dependencies
What I Build
Production-ready voice AI infrastructure that you own and control.
Speech-to-Text Pipeline
Self-hosted Whisper or Parakeet on GPU with sub-200ms latency. Multi-instance pools for concurrent calls. Phone audio preprocessing (8kHz mulaw to 16kHz PCM). Domain-specific keyword boosting.
LLM Inference
vLLM-powered inference with models sized for your use case. Continuous batching for high concurrency. I've run Qwen 0.5B to Llama 70B depending on quality vs latency needs.
Text-to-Speech
Kokoro or similar open models running locally. 50+ voice options, ~100ms latency. No per-character API costs eating your margins.
Telephony Integration
Twilio WebSocket streaming, SIP trunk connections, real-time audio handling. Half-duplex or full-duplex depending on your conversation flow needs.
Multi-Tenant Architecture
Database-backed config for custom prompts, voices, and keyword corrections per client. Admin UI for managing tenants without touching code.
Ready to Own Your Voice AI?
Let's talk about your requirements and see if self-hosting makes sense for your scale and use case.