Production Voice AI Agents Built with LiveKit
Sub-500ms voice response times. SIP telephony integration. Real-time WebRTC streaming. We build voice AI systems with LiveKit, Deepgram, Cartesia, and Twilio that work beyond the demo, from the first call to the millionth.
Built With
Recognized by Clutch
What We Build with LiveKit
From voice AI prototypes to production telephony systems handling thousands of concurrent calls.
Production Voice AI Agents
End-to-end voice pipelines using LiveKit Agents with Deepgram STT and Cartesia or Rime TTS. We build agents that listen, think, and respond in under 500 milliseconds, handling interruptions, turn-taking, and natural conversation flow that users expect from production voice systems.
SIP Trunking & Telephony Integration
Connect your AI agents to the phone network through LiveKit SIP and Twilio. We handle inbound and outbound calling, IVR replacement, call transfer to human agents, DTMF tone detection, and the telephony edge cases that only surface when real customers start calling.
Real-Time WebRTC Communication
Low-latency audio and video streaming built on LiveKit's WebRTC infrastructure. We implement browser-based voice interfaces, multi-party conferencing with AI participants, and real-time transcription overlays, all optimized for the latency constraints of live conversation.
Multimodal Voice Interfaces
Voice-first applications that combine speech with touch, text, and visual elements. We build accessible interfaces for iPads, kiosks, and web browsers where users can speak, tap, or type, and the AI responds through the most appropriate channel.
Voice Pipeline Observability
Full-stack monitoring of your voice AI system with LangFuse and Arize. We instrument every stage of the pipeline (STT latency, LLM inference time, TTS generation, WebRTC delivery) so you can identify bottlenecks, track costs per conversation, and catch quality regressions before users notice.
Edge & Cloud Voice Deployment
Deploy voice agents on cloud infrastructure for scale or on edge devices like Raspberry Pi and Mac Mini for low-latency local processing. We architect hybrid deployments where STT and TTS run at the edge while LLM inference happens in the cloud, optimizing for both cost and response time.
Why Voice AI Needs Senior Engineers, Not Tutorial Followers
A LiveKit voice agent demo takes an afternoon to build. A production voice system takes months of engineering decisions that determine whether your users have a conversation or a frustrating experience. The difference is in the details: how the system handles overlapping speech, what happens when the STT provider returns garbage during a noisy call, how the agent recovers when the LLM takes 3 seconds instead of 300 milliseconds, and how you debug a conversation that went wrong at 2 AM.
Voice AI has unique failure modes that text-based systems never encounter. Echo cancellation that works in a quiet office fails in a car with the windows down. Endpointing algorithms that detect when a user has stopped speaking need tuning per use case, because a 1-second pause means something different in a medical consultation than in a quick customer service call. SIP integration with telephony providers involves protocol-level debugging that most developers have never touched.
We shipped a production LiveKit voice assistant for Medicare patients in two weeks, from first line of code to real users on iPads. We actively contribute to the LiveKit open source community, file issues, and help other developers in the forums. When you hit a wall with LiveKit, we have likely already solved it, or we know the maintainers who can help.
Our Voice AI Tech Stack
The full stack for building, deploying, and monitoring production voice AI systems.
Voice AI Systems We Have Deployed
Production voice systems delivering measurable results for real users.
Voice AI for Medicare Patients
Built a LiveKit Agents voice assistant for Medicare patients on iPads. Deepgram STT and Cartesia TTS deliver sub-500ms response times. Multimodal interface combines voice with touch for accessibility, with full pipeline observability through LangFuse.
Read Case StudyAI-Powered Product Recommendation IVR
Replaced a rigid IVR menu tree with an AI-powered conversational system. Customers speak naturally instead of pressing buttons, and the system routes to the right product recommendations using real-time inventory data.
Read Case StudyVoice-Enabled Customer Support
Extended a text chatbot into a full voice channel using LiveKit. Customers call in, speak to an AI agent that handles 75% of requests autonomously, and get seamlessly transferred to a human agent with full conversation context when needed.
Read Case StudyHow We Work
From voice pipeline design to production deployment in weeks, not months.
Discovery Call
A 30-minute technical conversation about your voice AI use case. We discuss your telephony requirements, latency targets, expected call volumes, and integration points. We map out the voice pipeline architecture that fits your constraints.
Architecture Proposal
Within a week, we deliver a detailed proposal covering STT/TTS provider selection, LiveKit deployment topology, SIP integration design, and latency budget breakdown. You get a clear picture of how every millisecond is spent in the voice pipeline.
Build & Ship
We ship a working voice agent in the first two weeks, not a slide deck. Iterative development with weekly demos, progressive addition of telephony features, and full observability from day one so you can monitor every conversation in production.
Frequently Asked Questions
Ready to Build Production Voice AI?
Tell us about your voice AI project and we will respond within 24 hours with an initial assessment. Whether you need a new voice agent, SIP telephony integration, or help scaling an existing system.
Get a Free Assessment
Describe your voice AI project and we'll assess how LiveKit can power your production voice system.