Voice Agent Orchestrators Compared: Vapi vs Pipecat vs LiveKit with AssemblyAI

Vapi vs Pipecat vs LiveKit: Compare architecture, control, transport, pricing, and setup tradeoffs to choose the right platform for your voice AI use case.

By Kelsey Foster, Growth

Building a voice agent requires more than picking an LLM—you need an orchestration layer that connects speech recognition, language understanding, and speech synthesis in real time. But which orchestration layer? Vapi, Pipecat, and LiveKit are three of the most widely used platforms for this, and they take fundamentally different architectural approaches to the problem.

This article breaks down how each platform works, where they differ on transport, pipeline control, and speech recognition integration, and which use cases each one fits best. We'll also cover a fourth option that's gaining traction: skipping the orchestration layer entirely with a single API that handles the full Voice AI pipeline. Whether you're evaluating options for a new build or reconsidering your current stack, understanding these architectural trade-offs will help you make a more informed decision before you write a line of code.

What are Vapi, Pipecat, and LiveKit?

Vapi, Pipecat, and LiveKit are voice agent orchestration platforms—tools that help developers build software capable of speaking and listening in real time. All three connect the same core components: a speech-to-text model that hears the user, a large language model (LLM) that figures out what to say, and a text-to-speech model that speaks the response. But the way each platform connects those components is completely different, and that difference determines how much control you have over the conversation.

Here's a quick orientation before going deeper:

How Vapi, Pipecat, and LiveKit differ architecturally

The architectural differences between these three platforms come down to three questions: Who controls the pipeline? How does audio travel? And how deeply can you configure speech recognition?

Orchestration model—managed service, explicit pipeline, or room-based events

The orchestration model is the logic layer that decides when to listen, when to call the LLM, and when to speak. Each platform handles this differently.

Vapi manages the pipeline for you. You write a system prompt, select a voice, and configure your tools through the API. Vapi's infrastructure executes the STT→LLM→TTS loop automatically.

Pipecat makes the pipeline explicit. Every step—voice activity detection, streaming transcription, LLM call, speech synthesis—is code you write and control. You can insert logic between any two steps, run processes in parallel, or fork the conversation based on an intermediate result.

LiveKit uses an event-driven model. Your agent joins a WebRTC "room" as a participant, subscribes to audio tracks, and responds to events like "new transcription received." The flow isn't a linear pipeline—it's reactions to what happens in the room.

Transport layer—WebSockets, WebRTC SFU, and transport-agnostic pipelines

The transport layer is how audio physically travels between the user's device and your agent. It affects latency, reliability, and how the platform scales.

Vapi uses WebSockets for bi-directional audio. You never configure transport directly—it's handled by the platform.

Pipecat is transport-agnostic. You choose the transport, and the pipeline logic stays the same regardless of how audio arrives.

LiveKit runs on WebRTC with a Selective Forwarding Unit (SFU) architecture. LiveKit Agents are tightly coupled to this infrastructure.

STT, LLM, and TTS integration—pluggable components vs. configured providers vs. managed pipeline

This is the dimension that most directly affects conversation quality.

Vapi handles STT providers through API parameters. You pick a provider, and Vapi routes audio to it.

Pipecat treats STT as an explicit processor in your pipeline. You connect directly to a streaming transcription model.

LiveKit integrates STT through a plugin system. It's more structured than raw API calls but less granular than Pipecat's explicit pipeline.

When to choose Vapi, Pipecat, or LiveKit

The right platform isn't the one with the most features—it's the one that matches how much ownership your team wants over the conversation pipeline.

Choose Vapi for speed and managed infrastructure

Vapi is the right choice when time-to-production matters more than architectural flexibility.

Choose Pipecat for full pipeline control

Pipecat is the right choice when you need to own the conversation logic.

Choose LiveKit for multi-participant real-time sessions

LiveKit is purpose-built for scenarios where multiple people are in the same session.

Skip orchestration entirely: AssemblyAI's Voice Agent API

AssemblyAI's Voice Agent API is a single WebSocket connection that handles the full voice agent pipeline—speech understanding, LLM reasoning, voice generation, turn detection, and interruption handling.

Final words

The voice agent infrastructure landscape is splitting into two clear paths. On one side, orchestration frameworks like Pipecat and LiveKit give you full control over every component in the pipeline—ideal when you need to customize deeply or when your architecture demands it.

The interesting trend is that complexity is moving downward. A year ago, building any voice agent meant stitching together three or more providers. Today, teams can choose exactly how much of that plumbing they want to own—from all of it (Pipecat) to none of it (Voice Agent API).

Get your API key to integrate AssemblyAI with Vapi, Pipecat, or LiveKit—or skip orchestration entirely with the Voice Agent API. $4.50/hr, no credit card required to start.

Frequently asked questions

What is the main difference between Vapi and Pipecat?

Vapi is a managed platform that runs the voice pipeline for you—you configure it, Vapi executes it. Pipecat is an open-source Python framework where you write the pipeline yourself, step by step.

Can Pipecat and LiveKit be used together?

Yes. Pipecat is transport-agnostic, so it can run over LiveKit's WebRTC infrastructure using LiveKit's transport adapter.