You've probably seen the tutorials. "Add telephony to your AI agent using Twilio." They make it sound straightforward. Buy a number, set up WebSockets, integrate speech-to-text, pipe in text-to-speech, handle the call state.
Then you actually try it and spend three weeks debugging WebSocket connections, transcription lag, and audio quality issues — only to end up with something that mostly works and requires constant maintenance.
What Twilio Actually Requires for AI Voice
Here's what a Twilio-based AI voice setup really looks like:
- Number provisioning through Twilio. This part is actually easy.
- Media streams over WebSocket. You need a server that accepts bidirectional audio streams and handles disconnections gracefully. This is where most people get stuck.
- Speech-to-text service. Deepgram or AssemblyAI. Both require API integration, cost money, and add latency.
- Text-to-speech service. ElevenLabs (great but expensive), Cartesia (fast), or Polly (cheap but robotic).
- Orchestration layer. Custom code that ties it all together. Receive audio, send to STT, get transcript, send to AI model, get response, send to TTS, stream back. Handle errors at every step.
- Ongoing maintenance. Every service updates its API. Your integration breaks. You fix it. Repeat.
This isn't a weekend project. It's a multi-week engineering effort.
When Twilio Makes Sense
Twilio is right if you have a dedicated engineering team, need fine-grained control over the audio pipeline, handle extremely high call volumes where per-minute costs justify the investment, or already have Twilio integrated.
When Twilio Doesn't Make Sense
Twilio is wrong if you're a small team that can't dedicate someone to telecom infrastructure, need to launch quickly, want predictable costs without per-service billing from five different providers, or are building an AI-first product.
Most AI agent builders fall into this second category.
The AgentLine Approach
AgentLine was built specifically for AI agents. The entire stack — number provisioning, call routing, speech-to-text (via Deepgram), text-to-speech (via Cartesia), and event handling — is bundled into one API.
Your AI agent sends text. It gets text back. The platform handles everything in between.
Setup: sign up, get API key, create agent, buy number ($2.00 one-time), make a call. No WebSocket config. No STT/TTS provider selection. No custom orchestration code.
Cost Comparison
Twilio DIY stack at moderate volume: Twilio voice (~$0.014/min), Deepgram STT (~$0.006/min), ElevenLabs TTS (~$0.015/min), server hosting ($20-50/month), plus significant engineering time.
AgentLine: $0.10/min all-in (including STT and TTS). Number: $2.00 one-time. No server costs.
For low to moderate volume, AgentLine is cheaper because you're not paying for engineering time or server hosting. At very high volumes, DIY can be cheaper per-minute if you've already amortized the build.
The Real Question
Are you building a telecom company, or are you building an AI product? If the answer is the second one, use a tool built for AI agents. Don't become a telecom engineer by accident.