We build real-time AI agents on LiveKit Agents 1.x: speech in, an LLM in the middle, speech out, with video and screen-share when you need it. First pilot in –3 weeks, from $8K. Sub-500 ms voice-to-voice, semantic turn-taking, and native telephony — for 10 calls a day or 10,000.
If your agent has to listen, think, and talk back while the user is still moving — a support line, a sales qualifier, a tutor, an in-app copilot — LiveKit handles the transport and we build the agent on top.
A managed platform (Vapi, Retell, Bland) ships a demo in a day but locks your models, latency, and call data behind their stack. A custom LiveKit build gives you the pipeline, the vendors, and the data — and still launches in weeks, not quarters.
Managed platforms are a fine way to validate a script. The moment latency, model choice, telephony, or call-data ownership matters, the custom build wins — at any call volume. New to the trade-offs? See the complete LiveKit for AI agents guide, or compare transports in LiveKit vs Agora.
A real-time voice agent is a loop that has to close in under half a second, every turn. Here is the pipeline we build and where the milliseconds go.
Audio comes in over WebRTC. LiveKit’s semantic TurnDetector v1 decides when the user has actually finished — using intonation and rhythm, not just silence — so the agent stops interrupting and stops talking over the user.
Deepgram Nova-3 (or GPT-Realtime-Whisper) transcribes as the user speaks — about 6.84% WER on real-world audio, 36 languages. Partial transcripts stream to the LLM so it can start thinking early.
The LLM (gpt-realtime, Claude, or Gemini Live) decides what to say, calls your tools — book, look up, transfer — and pulls answers from your knowledge base over RAG. MCP tool-calling wires the agent to your systems.
Cartesia Sonic-3 or ElevenLabs Flash v2.5 starts speaking within ~75–90 ms, so the reply begins before the full sentence is generated — in your brand voice, your languages.
Audio streams back over WebRTC. If the user cuts in, barge-in stops playback instantly and the loop restarts. When the agent hits its limit, it transfers to a human over SIP with full context.
End to end, a well-tuned LiveKit loop answers in under 500 ms — the threshold where a conversation feels natural instead of robotic. Speech-to-speech models (gpt-realtime) shorten the loop further by skipping the separate STT and TTS hops.
LiveKit is the transport and orchestration layer. Around it we wire the models, telephony, data, and observability that turn a demo into something you can put on a phone line.
An inbound voice agent that answers FAQs, looks up account state via tools, and transfers to a human with context when it cannot resolve. Replaces hold queues.
Outbound or inbound agent that qualifies leads, books meetings on the calendar, and logs the call to your CRM over MCP.
A voice- and screen-aware agent embedded in your web or mobile app that walks users through tasks hands-free.
A multilingual tutor that listens, corrects, and adapts in real time; video and avatar optional for presence.
HIPAA-pattern voice intake, appointment reminders, and post-visit follow-up over the phone line.
Order-taking and front-line phone automation that understands interruptions and accents, with sub-500 ms turn-taking.
Managed voicebot platforms are built to demo fast. A custom build is built to be yours — your latency, your models, your data, your roadmap. Here is the honest split.
Not sure which side you are on? The free architecture review below will tell you straight.
We design and ship the whole pipeline end to end: transport, models, tools, telephony, eval, deploy. You get a production agent and the code.
You have an agent that is slow, talks over people, or hallucinates. We fix turn-taking, latency, and the eval gap, and harden it for production.
Our real-time engineers join your team and build alongside you, with LiveKit and the voice stack as their home turf.
Fixed-scope starting points for a LiveKit agent build. Every number is a floor you build up from, not a ceiling you are capped at.
Model and usage costs (LLM, STT, TTS, LiveKit) are billed at provider rates — no per-minute platform markup from us. We help you forecast them in the estimate.
Before you spend a dollar on the build, we will help you figure out whether it should exist and how it should be shaped.
Competitor analysis, core feature definition, monetization modeling, and a full launch blueprint — delivered within a week. Written by engineers who'll build what they plan.
An independent review of your system's technology choices, structural components, and workload fit — with a plain verdict on what's working, what's a liability, and exactly what to change to reach your goal. Delivered within a week.
A full audit of your code with every issue documented, evidenced, and located — exact file, exact line. Plus a system architecture review and a prioritized fix roadmap. Not a consultant's opinion. A case file. Delivered within a week.
A specialist review of your video or streaming product covering latency, media server architecture, WebRTC, playback reliability, real-time chat, and scalability. Every finding is specific, located, and fixable. Delivered within a week.
We are not a generalist shop that added a voice demo last quarter. Real-time audio and video has been the core of the business for 20 years.
Two decades shipping real-time media systems — not a pivot into this quarter’s trend.
We work in the same transport, SFU, and turn-taking layer agents run on, so the agent and the media stack are built by the same people.
Turn detection, STT, LLM, tools and RAG, TTS, telephony, eval — we build and tune every hop, and we will tell you the exact versions we run.
Sub-500 ms voice-to-voice is a target we engineer toward — semantic turn-taking, streaming STT, first-token and first-audio budgets.
Your code, your cloud, your call data, your eval set. No platform lock-in, no per-minute tax.
If a managed platform is genuinely the right call for your stage, we will say so on the first call.
The questions buyers ask before they build. The same answers power this page’s FAQ schema.
What is LiveKit AI agent development?
Why build on LiveKit instead of a platform like Vapi or Retell?
How low can the latency go?
Which models can the agent use?
Can the agent answer real phone calls?
Can it handle interruptions (barge-in)?
Can the agent use our data and tools?
Voice only, or video and multimodal too?
How long does a build take, and what does it cost?
Do we own the code and the data?
LiveKit for AI agents — the complete guide
Read the guide →Multimodal2026 LiveKit multimodal agents: voice, vision & production
Read the article →VoiceLiveKit AI agents: a build guide
Read the article →Related serviceAI software integration
See the service →VideoVideo AI agents: a build guide
Read the guide →Related servicePhone/PSTN call agents
See the service →Tell us what the agent needs to do. We will map the pipeline, name the models, and give you a timeline and a number — in one call. Building plain LiveKit infrastructure, or a phone-only call agent? See LiveKit development and AI call agents.
Specialist software house for video, real-time and AI products. Founded 2005. 50 in-house engineers.
