LiveKit
Build, test, and scale real-time voice, video, and robotics agents on an open-source framework with published per-minute inference pricing.
When real-time voice or video is the product rather than a feature bolted onto one, LiveKit is the platform we'd build on: own the agent code, pick any model from a published per-minute list, and start on a real $0 Build tier with no credit card. The published inference pricing makes cost forecasting possible at thousands of minutes per month. You pay for that control in engineering hours, so teams that need a drag-and-drop builder should look at Vapi or Retell instead.
Verified 5h ago · liveness 83/100 · cite: rightaichoice.com/tools/livekit
- Engineering teams building production voice AI agents with custom business logic
- Teams creating real-time video agents that need frame-level analysis
- Robotics companies requiring low-latency streaming for teleoperation or physical AI
- Enterprises deploying HIPAA or SOC 2 compliant conversational AI over phone and SIP
- Non-technical users who need a no-code agent builder
- Teams wanting a black-box managed agent with no infrastructure thinking
- Simple static video streaming with no AI logic involved
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Skip LiveKit if you need a drag-and-drop agent builder or a fully managed black box — building here means writing Python or Node.js, and your final per-minute cost is the sum of LLM, STT, TTS, telephony, agent session, and observability meters.
Every phone call meters agent session at $0.0100/min, telephony at $0.0100/min, and observability at $0.0100/min on top of your STT, TTS, and LLM usage — that's $0.03/min before any model runs.
Build is genuinely free with no credit card, which is rare among voice agent platforms and makes it the cheapest credible starting point. Ship at $50/mo suits a team past prototype; Scale at $500/mo is where inference discounts, region pinning, and HIPAA/security reports appear — the tipping point is when per-minute savings exceed $450/mo. Contact-sales enterprise pricing adds volume inference discounts and SSO. Compared with per-minute bundled voice APIs, LiveKit's itemized model list is more
In short
LiveKit — Build, test, and scale real-time voice, video, and robotics agents on an open-source framework with published per-minute inference pricing. Best for Engineering teams building production voice AI agents with custom business logic, Teams creating real-time video agents that need frame-level analysis, Robotics companies requiring low-latency streaming for teleoperation or physical AI. Free to start; paid plans from $50/mo.
No head-to-head comparison for LiveKit yet — the alternatives below are the closest matches we list.
What's new in LiveKit
Checked 7 days agoAcross the latest 10 updates: 4 feature updates, 3 launches, 1 pricing change, 1 community discussion and 1 news mention.
Testing voice agents with Agent Simulations
LiveKit details Agent Simulations for testing voice agents before production.
How Serve AI shipped a better voice agent with Agent Simulations
LiveKit publishes a customer case study on Serve AI using Agent Simulations to improve its voice agent.
Retell vs. Vapi vs. LiveKit for voice AI agents: A comparison for developers
LiveKit publishes a developer comparison of Retell, Vapi and LiveKit for voice AI agents.
Introducing Private Links on LiveKit
LiveKit launches Private Links, adding private connectivity for LiveKit deployments.
Introducing the LiveKit Startup Program: Your whole stack, on us
LiveKit opens a Startup Program offering its full stack to early-stage companies.
Test your voice agents with non-production deployments
LiveKit adds non-production deployments so teams can test voice agents in isolation.
Introducing LiveKit Connectors: voice agents where people already talk
LiveKit launches Connectors, placing voice agents into existing communication channels.
Introducing per-second metering for LiveKit
LiveKit moves to per-second metering, changing how usage is billed.
Introducing PII redaction for LiveKit Observability
LiveKit adds PII redaction to its Observability tooling for voice agent logs.
Making voice agents sound human with expressive mode
LiveKit ships expressive mode for more natural-sounding voice agents.
What people actually say about LiveKit — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
79 mentions across 6 sources (Hacker News, YouTube, Product Hunt, App Store, Stack Overflow, Lemmy) · researched Aug 30, 2026.
Average across the 6 sources that answered — each source counts once, not each post.
- +Open-source with no vendor lock-in; take your code anywhere.
- +Multi-language SDKs: Python, Node.js, C++, Unity for any stack.
- +Global edge network keeps latency under 1000ms for real-time interactions.
- +Inference gateway integrates 100+ TTS, LLM, and STT models.
- +Production-ready features like Turn Detector v1.0 enhance voice interactions.
- −Steep learning curve for non-engineers or those new to WebRTC.
- −Per-minute costs not always clear upfront; can surprise users.
- −Offline deployment requires a powerful computer.
- −Limited no-code flexibility compared to Vapi or Bland AI.
- −Customer support may be slower for open-source community users.
- • Per-minute session costs can add up with premium models (TTS/LLM/STT) used through the inference gateway.
- • Standard support may be limited; paid plans are needed for faster response times.
- • Self-hosting requires infrastructure costs (bandwidth, compute) not covered by the platform.
Viability Score
How well maintained and how widely used is LiveKit? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Open-source agents framework in Python and Node.js for real-time voice and video agents
- Voice AI agents with automatic turn detection and interruption handling
- Video AI agents with per-frame video metadata for real-time analysis
- Physical AI and robotics streaming, including teleoperation via LiveKit Portal
- Inference gateway routing to 100+ hosted LLM, STT, and TTS models
- Published per-minute, per-model pricing for LLM, STT, and TTS inference
- Per-second metering for finer-grained usage billing
- Telephony via phone numbers and SIP, with 1 free number on Build
- LiveKit Connectors for placing voice agents inside chat and messaging surfaces
- Agent Simulations for testing voice agents before production
- Non-production deployments for isolated voice agent testing
- Private Links to restrict room and media access to private network paths
- PII redaction in LiveKit Observability logs and session traces
- Expressive mode for more natural-sounding voice output
- Multi-language SDKs including Python, Node.js, C++, and Unity
About LiveKit
LiveKit gives engineering teams the plumbing for real-time voice and video AI: an open-source agents framework, a managed cloud for deployment and scaling, an inference gateway, and telephony over SIP. You define a session in Python or Node.js — stt, llm, tts, turn detection — and write the business logic around it. The vendor's quickstart claims a working voice agent in under 10 minutes, and OpenAI built ChatGPT's Advanced Voice on LiveKit Cloud. The stack splits into four parts. The open-source framework handles agent code and testing. The inference gateway routes to hosted LLM, STT, and TTS models with per-minute rates published openly, from GPT-5 nano at $0.0002/min up to OpenAI GPT Realtime at $0.0676/min. LiveKit Cloud runs the agents on a global edge network, and telephony adds phone numbers and SIP for inbound and outbound calls. Automatic turn detection, interruption handling, and WebRTC transport are handled for you, and per-second metering replaced coarser billing increments in August 2026. Recent releases target pre-launch pain rather than demo polish: Agent Simulations for testing voice agents (with a Serve AI case study), non-production deployments for isolated testing, Private Links for private connectivity, LiveKit Connectors for putting voice agents inside chat surfaces, PII redaction in Observability logs, and an expressive mode for more natural-sounding voices. A Startup Program opened in September 2026. Compliance runs to GDPR, SOC 2 Type 2, and HIPAA, with 99.99% uptime and roughly 100ms global latency claimed. Compared with no-code builders like Retell or Vapi, you trade engineering hours for control of every layer of the agent loop and a transparent per-minute cost model. The open-source framework is the hedge: if the hosted platform stops fitting, your agent code still runs.
Behind the Verdict
Pick LiveKit when the agent is the business, not a widget. A voice agent handling real phone calls, a video agent reading frames, or a robotics pipeline that cannot tolerate jitter — these are the shapes where owning the transport, agent loop, and model routing pays off. In practice the per-minute math is the real argument: at scale, shaving Deepgram Nova-3 from $0.0048/min on Build/Ship to $0.0042/min on Scale compounds, and swapping a TTS provider is a config or code change rather than a platform migration. Pass on it if nobody on the team wants to write Python or Node.js. The framework is deliberately minimal, which means the surrounding work — prompt handling, tool calls, fallback logic, evals — is yours. Teams that want a builder with a dashboard and a bundled invoice will get to production faster on Retell or Vapi, and LiveKit's own comparison post makes that trade honestly. The closest alternative is not another SDK but a different posture: a managed agent platform hides the transport and the model routing, while LiveKit exposes both. That control cuts both ways. You get model choice and cost visibility; you also inherit responsibility for agent quality, and the observability and testing tooling around it only recently caught up. Watch the cost composition, not just the headline inference rate. The pricing calculator previews an agent session at $0.0100/min before you add LLM, STT, TTS, telephony, and observability, so a nominal $0.0479/min total can drift once you pick a frontier model. Realtime models like OpenAI GPT Realtime at $0.0676/min or Gemini Live 2.5 Flash at $0.0144/min change the shape of a budget fast. Agent Simulations and non-production deployments matter more than they sound. Voice agents fail in ways unit tests miss — barge-in, dead air,
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Real-world workflow fit
Concrete scenarios for the personas LiveKit actually fits — and what changes day-one when you adopt it.
Writes a Python AgentSession declaring AssemblyAI Universal-3.5 Pro Streaming for STT, Gemma 4 31B for the LLM, and a Cartesia voice for TTS, runs it locally, then deploys to LiveKit Cloud on the free Build plan.
Outcome: A working voice agent in the browser in under 10 minutes, with session metrics visible in observability and no credit card on file.
Ports a phone IVR to LiveKit with SIP telephony, tests changes on non-production deployments, then ships with instant rollback armed and PII redaction enabled on observability logs.
Outcome: Phone calls answered by the agent at a forecastable per-minute cost, with the ability to revert a bad agent deployment instantly and store traces without user PII.
Streams camera video and voice commands from a robot over WebRTC, and uses LiveKit Portal for teleoperation and data collection during physical AI training.
Outcome: Low-latency remote operation and a captured training dataset without building custom realtime transport.
Use Cases
- Build a voice agent that answers phone calls and automates customer service with live interruption handling.
- Create a real-time video analysis agent that processes frames from a camera and provides spoken feedback.
- Deploy a telephony-based appointment booking bot with IVR replacement using the handoff pattern.
- Route phone and web traffic through the inference gateway and pick the cheapest STT, LLM, and TTS per workload.
- Test agent changes on non-production deployments before they touch live callers.
- Place a voice agent inside an existing chat or messaging surface using LiveKit Connectors.
- Stream video and voice commands to a physical robot over WebRTC.
- Run observability with PII redaction so session traces can be stored without exposing user data.
Models Under the Hood
as of 2026-10-16
Limitations
- LiveKit is an open-source framework plus developer platform: the homepage examples are code (agent.py, visualizer.tsx) and the quickstarts assume Python or Node.js coding skills, so non-technical teams can't ship here.
- Cost is usage-based and additive — the pricing calculator's own example totals $0.0479/min for a phone call, combining agent session ($0.0100/min), telephony ($0.0100/min), observability ($0.0100/min), plus STT ($0.0075/min) and TTS ($0.0090/min) before LLM inference is added.
- Telephony minutes are billed on top of agent session minutes, and the free Build tier includes only 1 free number.
- Advanced enterprise controls — HIPAA and security reports, region pinning, role-based access, metrics export APIs, SSO and a support SLA — are positioned at Scale and Enterprise, so compliance-sensitive buyers can't stay on Build or Ship.
as of 2026-10-01
Verification history
We have re-verified LiveKit 21 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 21 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published LiveKit tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Build
$0/mo
Ideal for
Individual developers and small teams validating a first voice or video agent without spending anything or entering a card.
What this tier adds
Starting tier: agent deployment, observability, inference credits, global edge network, session metrics, and telephony with one free number.
Ship
Starting at $50/mo
Ideal for
Startups putting a voice agent in front of real users for the first time and needing seats for a small team.
What this tier adds
Adds team collaboration, custom voices, instant rollback to a previous agent deployment, and email support over Build.
Scale
Starting at $500/mo
Ideal for
Growth-stage companies running high call volume that need compliance artifacts, regional control, and cheaper per-minute inference.
What this tier adds
Adds role-based access, metrics export APIs, region pinning, Private Links, security reports and HIPAA, plus inference discounts versus Build/Ship rates.
Enterprise
Custom
Ideal for
Large organizations needing volume contracts, SSO, and a contractual support commitment.
What this tier adds
Adds volume pricing including inference, a shared Slack channel, SSO, and a support SLA on top of Scale.
Where the pricing makes sense
The company stage and team size where LiveKit's pricing actually pencils out — and where peers do it cheaper.
Build is genuinely free with no credit card, which is rare among voice agent platforms and makes it the cheapest credible starting point. Ship at $50/mo suits a team past prototype; Scale at $500/mo is where inference discounts, region pinning, and HIPAA/security reports appear — the tipping point is when per-minute savings exceed $450/mo. Contact-sales enterprise pricing adds volume inference discounts and SSO. Compared with per-minute bundled voice APIs, LiveKit's itemized model list is more
Setup time & first value
How long it actually takes to get something useful out of LiveKit — broken out by persona, not the marketing-page minute.
Engineers following the Python or Node.js quickstart can have a voice agent talking in under 10 minutes; adding a web or mobile front end and telephony is a short afternoon. Standing up production-grade work — compliance controls, region pinning, observability policies — depends mostly on which tier you need (Scale for HIPAA and security reports), not on LiveKit's onboarding.
Switching to or from LiveKit
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a homegrown WebSocket stack: replace custom realtime transport with LiveKit Cloud, keeping your agent logic and adding telephony as a unified export interface across web and phone calls.
- →From a no-code voice builder: port prompts and flows into the open-source agents framework in Python or Node.js, then pick STT/LLM/TTS per model from the inference gateway.
- →From Twilio-only telephony: keep Twilio as the carrier integration while moving session handling and turn detection to LiveKit.
- →From a single-vendor voice API: declare your existing LLM, STT, and TTS in an AgentSession and compare the itemized per-minute bill against your bundled rate.
- ↗To a no-code builder (Vapi, Bland): rebuild flows in a drag-and-drop UI, trading model control and itemized pricing for faster iteration by non-engineers.
- ↗To self-hosted open source: the agents framework is open source, but you take on realtime transport, scaling, and observability that LiveKit Cloud currently handles.
- ↗To a direct model provider: call STT, LLM, and TTS vendors yourself and drop the inference gateway, absorbing the integration and pricing-comparison work LiveKit does for you.
Integrations
Resources & Guides
- Resourcelivekit.io
Layered Caller Verification Guide
Helpful link from livekit.io
- Resourcelivekit.io
Pipeline Vs Realtime Guide
Helpful link from livekit.io
- Resourcelivekit.io
Debug Voice Agents Agent Console
Helpful link from livekit.io
- Resourcelivekit.io
Voice Agent Latency Guide
Helpful link from livekit.io
- Resourcelivekit.io
Bring Langchain Agents To Livekit
Helpful link from livekit.io
- Resourcelivekit.io
The Handoff Pattern for Voice Agents That Replaces IVR Menus
Build voice agents that replace IVR menus with an LLM triage agent that routes calls to specialist AI agents or humans with full context and seamless transfers.
- Resourcelivekit.io
Human In The Loop Pattern
Helpful link from livekit.io
- Resourcelivekit.io
The ReAct Pattern for Voice Agents and How AI Agents Think, Act, and Respond
Learn the ReAct pattern for voice agents. See how Think, Act, Observe loops power tool calling so your agent can use APIs, databases, and workflows to solve real requests.
- Resourcelivekit.io
Sequential Pipeline Architecture
Helpful link from livekit.io
- Resourcelivekit.io
Collect Structured Data Livekit Agents
Helpful link from livekit.io
Tutorials & Learning
YouTube returned 6 videos for “LiveKit”, and we withheld 6: 6 could not be judged, because “LiveKit” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about LiveKit.
Official links
Tools that pair well with LiveKit
Common stack mates teams adopt alongside LiveKit, with the specific reason each pairing earns its keep.
ElevenLabs
ElevenLabs AI voice generator turns text into speech in 90+ languages, with cloning, dubbing, music and voice agents.
Presto Voice
Presto Voice is drive-thru voice AI that takes QSR orders and upsells every car at the speaker post.
Deepgram
Deepgram's speech-to-text API pairs Flux STT conversation-aware transcription with Flux TTS and a single Voice Agent API call.
Alternatives to LiveKit
View allElevenLabs
ElevenLabs AI voice generator turns text into speech in 90+ languages, with cloning, dubbing, music and voice agents.
Presto Voice
Presto Voice is drive-thru voice AI that takes QSR orders and upsells every car at the speaker post.
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