How AI Phone Answering Actually Works Under the Hood

How AI Phone Answering Actually Works Under the Hood I've been deep in the AI voice space for a while now, and the amount of misconception about what "AI phone answering" actually means is wild. Let me break down the tech stack. The Architecture A modern AI phone answering system has roughly 4 layers: Caller → Telephony (SIP/PSTN) → STT Engine → LLM → TTS Engine → Caller Layer 1: Telephony You need a phone number that routes to your system. Most use SIP trunking providers (Twilio, Telnyx, Vonage). The audio comes in as RTP streams. Layer 2: Speech-to-Text (STT) Real-time transcription. Deepgram and AssemblyAI dominate here. Latency is critical — you need sub-300ms or the conversation feels laggy. Whisper is great for batch but too slow for real-time without heavy optimization. Layer 3: The Brain (LLM) This is where the magic happens. The LLM gets: The transcribed speech Business context (hours, services, pricing, FAQs) Conversation history Available actions (book appointment, transfer