Real-Time Voice Transcription for Your AI Agent — Without the Plumbing

When you build an AI agent that handles voice calls, you quickly hit a wall: how do you get the spoken words into your AI's context in real time? The naive path is painful. You stand up a WebSocket server, ingest raw RTP packets, decode the audio codec, buffer frames, feed them into a speech-to-text engine, manage partial vs. final transcripts, and somehow do all of this while also running your actual AI logic. Oh, and latency matters — callers don't wait 3 seconds between sentences. This post shows how to skip all that plumbing and get real-time transcription piped directly into your AI agent using VoIPBin . The Problem With DIY Transcription Let's be concrete. Here's what a "simple" DIY voice pipeline looks like: Caller → SIP → RTP stream → your server ↓ decode opus/PCMU ↓ buffer + VAD detection ↓ STT API (Google/AWS/Deepgram) ↓ handle partial transcripts ↓ your AI logic ↓ TTS → re-encode audio → RTP back Each step is a failure point. Each step adds latency. And none of it is your ac