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} {status === "active" && (Session ended.
}sip\_outbound\_trunk\_id).
Configure this in the Dashboard Telephony page and attach it to your agent.
Keep your models. Keep your orchestrator. The execution layer sits between them and cuts cost and latency on every turn.
Teach your coding agent to build with SLNG, or send your first request by hand.
Your orchestrator, your prompts, and your tools stay exactly as they are. Repoint your speech calls at SLNG, and routing, caching, and failover happen behind the endpoint.
Text in, audio out. Multiple voices and languages, over HTTP or streaming WebSocket.
Transcribe audio files or live streams. Single-language or auto-detect across 10+ languages.
An LLM paired with STT and TTS that takes and makes phone calls or runs in the browser.
A 16-turn call makes 48 model calls. By default each one runs from scratch, even for a greeting you have synthesized a thousand times. The execution layer changes that across three stages.
Route input to the right transcription model, based on language, accent, noise, and cost.
Decide whether a turn needs full LLM reasoning, local inference, or no inference at all.
Assemble TTS output from cache and synthesis. Don't generate what already exists.
Run SLNG inside the agent framework you already use. Same endpoints, native adapters.
Bring your own provider keys and route across 30+ speech models over standard HTTP and WebSocket, without changing your integration.
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