Before we jump into specific tools, it's crucial to understand the fundamental components that make up a voice AI agent. Think of it as a voice AI agent sandwich architecture, with several layers working in harmony:

Speech-to-Text (STT): Converts spoken words into text.
Large Language Model (LLM): Processes the text, understands intent, and generates a textual response.
Text-to-Speech (TTS): Converts the LLM's text response back into natural-sounding speech.
Orchestration/Call Management: Manages the flow of conversation, handles interruptions, and connects the different components.
Integrations: Connects the agent to CRMs, databases, or other business systems.

This core architecture applies whether you're using a fully managed platform or building a voice AI agent with deepgram and elevenlabs for STT/TTS and an open-source LLM for processing.