The global execution layer for real-time voice
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.
Plug in the endpoints. Nothing else changes
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.
Three primitives for real-time speech
Text-to-Speech
Text in, audio out. Multiple voices and languages, over HTTP or streaming WebSocket.
Speech-to-Text
Transcribe audio files or live streams. Single-language or auto-detect across 10+ languages.
Voice Agents
An LLM paired with STT and TTS that takes and makes phone calls or runs in the browser.
Every turn takes the path it actually needs
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.
STT routing
Route input to the right transcription model, based on language, accent, noise, and cost.
Tiered decisioning
Decide whether a turn needs full LLM reasoning, local inference, or no inference at all.
Output assembly
Assemble TTS output from cache and synthesis. Don’t generate what already exists.
Drops into your orchestrator
Run SLNG inside the agent framework you already use. Same endpoints, native adapters.
Works with the models you already use
Bring your own provider keys and route across 30+ speech models over standard HTTP and WebSocket, without changing your integration.
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