—— Platform comparison
SignalWire vs.
LiveKit
LiveKit gives you a WebRTC media server and an agent framework, with carrier reach assembled from partners. SignalWire owns the telecom underneath: SIP and PSTN it runs itself, transfers that keep context, and the AI kernel inside the media engine.
SignalWire positioning
A different philosophy: own the interaction, don't just transport it.
Communications has never had a control plane: a layer that owns interaction state, lifecycle, routing, and outcomes. CPaaS gave developers APIs but pushed state management, transfer logic, and compliance logging back onto every customer. SignalWire is defining Programmable Unified Communications: the missing layer.
One carrier-grade orchestrator holds call state and AI-engine state in sync, with the AI kernel embedded inside the media engine. Built by the FreeSWITCH team, the same technology powering major UCaaS and CCaaS platforms for two decades. Most voice AI is "prompt and pray," behavior governed by prompts alone. SignalWire's System-Directed AI constrains the model with code: scoped tools, step machines, and validation before execution. The AI can't leak what it doesn't know or break rules it doesn't enforce. Trusted across 2,700+ companies and 2.7 billion minutes and messages annually.
Where the architecture differs
What LiveKit does well and where the architecture differs.
What LiveKit does well
LiveKit is a strong WebRTC media server with an open-source agents framework. For browser- and app-based real-time audio and video, it is well-built, well-documented, and fast to prototype on.
The structural difference
LiveKit reaches the phone network through partners and bridges: SIP bridged on top, PSTN via carrier partnerships, agent state in infrastructure you run yourself. SignalWire is telecom-native: SIP, PSTN, and WebRTC are first-class in the same media engine, and transfers carry context because the platform owns the call state.
Side by side
SignalWire vs. LiveKit, category by category.
The scannable verdict, with the receipts. Every claim traces to a source.
Migration
Migrating from LiveKit
Most LiveKit migrations are about deleting infrastructure, not rewriting agents.

Customer proof
2,000+ companies build on SignalWire

Does SignalWire support SIP and PSTN natively?
Yes. SIP, PSTN, and WebRTC are first-class protocols in the same media engine, with production-grade support for transfers, DTMF, and recording. LiveKit's SIP is bridged on top of a WebRTC core and its PSTN runs through carrier partnerships; SignalWire owns the substrate, so there is nothing to bridge.
Do I need Redis or load balancers to run agents on SignalWire?
No. SignalWire agents are stateless and serverless. Each agent is a self-contained web app and HTTP endpoint. Transfers happen by URL and carry context, so there are no long-lived sessions, sticky connections, or memory leaks to manage.
What does SignalWire's Agents SDK include out of the box?
Prefab agent templates with structured prompts, guardrails, and goals; built-in retrieval; multi-agent orchestration; real-time logging; and a testing framework. Prefabs deploy in minutes and can be subclassed or overridden entirely.
Can I run LiveKit and SignalWire in parallel during migration?
Yes. Number porting is supported, and both platforms can run side by side during cutover. Most teams move traffic gradually, starting with a single number or queue, so there is no flag-day risk.
How does SignalWire's pricing compare to LiveKit?
SignalWire bills one transparent rate: about $0.16/min for the AI runtime, roughly $0.163 to $0.168 all-in once transport is included. A LiveKit stack adds telephony billed separately through carrier partners, on top of your own STT, LLM, and TTS vendors, so the all-in number is usually higher than the headline.
How does SignalWire measure its latency claims?
With the open-source latency_checker, which measures the full conversational round-trip on stereo recordings, not a single model hop. Typical turns land around 1200ms, 800ms on an optimized stack, and 600ms with speech-to-speech models. Be skeptical of sub-500ms claims that measure only part of the path.




