Telephony & VoIP Solutions at Scale

Traditional telephony often processes audio sequentially. Voice AI requires a different model because the system must listen, reason, and respond while the call is still active.

When a call is established, FreeSWITCH's media bug API forks the audio stream into two independent channels: caller audio and agent or callee audio. Each direction is encoded as raw PCM Linear16 at 8kHz or 16kHz.

The audio is pushed over a persistent WebSocket connection to a streaming backend built with Python, FastAPI, or Node.js. That backend sends speech to an STT service, passes the transcript to an LLM, receives response text, and converts it back to audio with TTS.

The synthesized response is injected back into the FreeSWITCH channel. With pre-warmed services, local buffering, and GPU-adjacent inference, the caller-to-AI response path can stay under strict latency budgets.

Voice quality depends on codec selection, jitter buffer behavior, packet loss, network path quality, and whether the platform avoids unnecessary transcoding.

We configure FreeSWITCH deployments to negotiate the right codec per call leg. Internal LAN calls often use G.722 or Opus for clarity. PSTN interconnects typically use G.711 μ-law or A-law to avoid avoidable transcoding latency.

For WebRTC browser clients, Opus is usually the best fit because it adapts well to changing network conditions. Jitter buffers are then tuned by workload: aggressive for low-latency AI calls and more conservative for traditional business calls.

We also implement SRTP encryption with DTLS-SRTP for WebRTC endpoints and SDES where SIP trunks require it. The goal is secure media transport without degrading call quality.