Choosing a voice agent stack is not a provider comparison exercise. It is an architecture decision about speed, control, latency, channel, and operational risk.
Step 1: Pick The Channel
The channel narrows the stack:
- Browser voice: WebRTC and web SDKs matter.
- Mobile voice: native audio permissions and SDK quality matter.
- Phone: SIP, PSTN, numbers, transfer, and recording consent matter.
- Contact center: CRM, QA, routing, and human agent workflows matter.
A stack that is great for a web demo may be weak for phone deployment.
Step 2: Choose Control Level
Managed voice platform
Use this when time-to-first-call matters most. Examples include Vapi, Retell AI, Bland AI, ElevenLabs Conversational AI, and Hume EVI.
Tradeoff: fast setup, less low-level control.
Open-source framework
Use this when you want composability and provider choice. Examples include LiveKit Agents and Pipecat.
Tradeoff: more control, more engineering.
Realtime model API
Use this when you want speech-to-speech or multimodal sessions with fewer pipeline components. Examples include OpenAI Realtime, Gemini Live, and Amazon Nova 2 Sonic.
Tradeoff: natural interaction, provider-specific session model.
Infrastructure-first stack
Use this when realtime media quality, scale, and channel control are central. Examples include Agora, LiveKit, Daily, Twilio, Telnyx, and SignalWire.
Tradeoff: strong transport foundation, but you still own agent behavior.
Step 3: Measure The Right Things
Do not optimize only model quality. Voice UX depends on:
- End-of-turn delay.
- LLM time to first token.
- TTS time to first byte.
- Barge-in response time.
- STT stability.
- Tool success rate.
- Cost per completed task.
- Human handoff rate.
Step 4: Check Operational Fit
Ask:
- Can you inspect transcripts and traces?
- Can users interrupt naturally?
- Can you control tool permissions?
- Can you transfer to a human?
- Can you meet recording and disclosure requirements?
- Can you change providers later?
- Can you explain failures?
Recommendation For Beginners
If you need to learn, build one managed-platform demo and one framework-based demo. The managed demo teaches product flow. The framework demo teaches the pipeline. Together they make stack tradeoffs much clearer.