Private AI voice system that lets you change speech providers without rebuilding the whole workflow

Voice features and AI workflows can leak sensitive user input when provider routing, credentials, and system boundaries are set up poorly. This platform had to support AI voice features while protecting user data and leaving room to change providers later.

The system sends sensitive voice traffic through a protected relay instead of exposing providers directly to the client. The speech pipeline was designed so STT, LLM, or TTS providers can be replaced without rewriting everything. Backend services were defined through clear contracts, and the desktop/cloud split lets latency-sensitive voice processing run locally while licensing, usage tracking, and provider sessions stay under backend control.

Designed for sensitive AI voice work: private data handling, easy switching between providers, secure relay services, a split desktop/cloud setup, and clear API contracts for how systems connect.

This case shows how to build an AI voice system that protects sensitive input, keeps provider options open, separates local and cloud responsibilities, and accounts for licensing, operational control, and future growth.

Relevant if you are building an AI product that handles sensitive user input, works with several providers, includes voice features, spans desktop and cloud, or needs strong privacy controls from the start.