H
    Hestur
    Platform / LiveKit

    Expert LiveKit
    Development

    We build production LiveKit systems — multi-agent voice pipelines, SIP telephony, WebRTC rooms, and OpenAI Realtime API integrations. The platform that beats every managed solution above 10k minutes/month.

    Sub-300ms voice latency10k+ min/monthWebRTC + SIPOpen-source SDK
    What We Build

    Six Production-Grade
    LiveKit Use Cases

    Multi-Agent Voice Pipelines

    Supervisor agents that route inbound calls to specialist sub-agents — triage → scheduling, intake → billing, receptionist → clinical team. Each agent has its own pipeline and prompt; LiveKit passes room context and transcript history between handoffs.

    Healthcare, insurance, legal, financial services

    Sub-300ms handoff latency between agents

    SIP Telephony at Scale

    Full PSTN coverage via LiveKit SIP module — inbound and outbound calling over Twilio, Vonage, or Bandwidth trunks. We configure codec negotiation, DTMF handling, call recording, and real-time transcription at the SIP layer.

    Contact centres, outbound sales, healthcare scheduling

    10k–200k+ minutes/month without per-minute platform fees

    Video + Voice Rooms

    Combined video and voice experiences: telehealth consultations with AI scribing, live customer support with screen share, multi-participant rooms where an AI agent attends alongside human participants.

    Telehealth, EdTech, customer success, remote support

    WebRTC rooms with AI participants at <150ms A/V latency

    OpenAI Realtime API Integration

    GPT-4o Realtime runs directly inside a LiveKit Agents worker — native audio in/out, zero intermediate transcription step, ultra-low latency responses, and built-in voice activity detection. The fastest voice AI architecture available.

    SaaS voice features, consumer apps, high-frequency call centres

    First-word latency under 200ms with Realtime API

    Custom Agent Frameworks

    Beyond the default VoicePipelineAgent — we build custom plugin pipelines for non-standard audio processing, multi-modal agents that combine voice with vision (GPT-4o Vision), and worker pools for high-concurrency deployments.

    Enterprise SaaS, security, logistics, field services

    Horizontal scaling via LiveKit Workers + Kubernetes

    Browser & Mobile WebRTC

    LiveKit JS/Swift/Kotlin SDKs wired directly into your web app or mobile product — real-time audio rooms, AI participants, push-to-talk interfaces, and live transcription overlays without a third-party platform in the loop.

    Consumer apps, internal tools, mobile-first products

    Direct browser-to-agent WebRTC, no SIP hop needed

    Architecture Spotlight

    OpenAI Realtime API
    on LiveKit

    The fastest voice AI architecture available — GPT-4o native audio, zero intermediate transcription, sub-200ms first-word latency.

    Standard Pipeline (Vapi / Retell)

    Microphone audio

    → STT (Deepgram) — 60–120ms

    → LLM (GPT-4o) — 200–600ms

    → TTS (ElevenLabs) — 100–200ms

    → Speaker output

    Total: 360ms–920ms per turn

    Realtime API on LiveKit

    Microphone audio

    → LiveKit room (WebRTC transport)

    → GPT-4o Realtime WebSocket

    (audio in → audio out, no text hop)

    → LiveKit audio track → speaker

    Total: 150ms–250ms per turn

    Native voice activity detection

    GPT-4o Realtime handles interruption natively — no separate VAD module, no endpointing tuning. The model knows when the user is done speaking.

    No transcription latency tax

    The standard STT → LLM → TTS chain adds 300–700ms per turn. Realtime eliminates the STT step entirely — audio goes straight to the model and comes back as audio.

    LiveKit as the WebRTC transport

    LiveKit handles room management, participant tracking, TURN/STUN, audio mixing, and recording. The Realtime API just handles AI processing. Best-of-both-worlds architecture.

    Fallback pipeline included

    We build a hot-standby STT → LLM → TTS pipeline that activates if Realtime API is rate-limited or degraded. Zero-downtime failover, invisible to the caller.

    Why LiveKit Wins at Scale

    The 10k Minute Crossover

    Below 10k minutes/month, Vapi BYOK is the right choice. Above it, LiveKit infrastructure costs collapse while managed platform fees keep compounding.

    PlatformCost/min10k min/month50k min/monthNote
    Managed (Vapi/Retell bundled)$0.45–0.60/min$4,500–6,000$22,500–30,000No infra control
    Vapi BYOK$0.23–0.33/min$2,300–3,300$11,500–16,500Best-in-class managed
    LiveKit Cloud + providers$0.05–0.10/min$500–1,000$2,500–5,000Our crossover recommendation
    LiveKit self-hosted + providers$0.02–0.04/min$200–400$1,000–2,000Maximum cost control

    < 10k min/month

    Use Vapi BYOK

    LiveKit infra setup cost outweighs per-minute savings at low volume.

    10k–50k min/month

    LiveKit Cloud

    Managed LiveKit eliminates infra ops while cutting costs 5–10×.

    50k+ min/month

    LiveKit self-hosted

    At scale, self-hosted LiveKit on Kubernetes is $0.02–0.04/min total.

    Architecture Deep-Dive

    Multi-Agent Handoffs

    LiveKit is the only voice AI platform with a first-class multi-agent architecture. We design and build agent topologies that standard managed platforms cannot support.

    Supervisor Pattern — Healthcare Example

    Inbound call → Room created

    → Receptionist Agent joins

    "How can I help you today?"

    → Caller: "I need to see Dr. Chen"

    → AgentHandoff triggered

    context = { name, intent, caller_history }

    → Scheduling Agent joins room

    Receptionist leaves gracefully

    → "I have you as [Name]..."

    No repeat of earlier context

    → Appointment booked → room closed

    Triage → Specialist

    A triage agent collects the reason for contact and routes to the appropriate specialist agent (billing, scheduling, clinical, complaints). Each specialist has a tailored prompt and tool set.

    Supervisor → Worker

    A supervisor agent orchestrates multiple worker agents running in parallel — one handling transcription, one doing real-time CRM lookup, one managing the conversation. LangGraph-like coordination over voice.

    Human-in-the-Loop

    An AI agent handles the conversation until a human expert is needed. The human joins the LiveKit room (as a participant), reviews the conversation summary, and takes over seamlessly — or provides a whisper prompt the AI agent reads aloud.

    Technical Scope

    What We Implement

    CapabilityLiveKitImplementation notes
    VoicePipelineAgent (STT → LLM → TTS)Core pipeline, all providers
    OpenAI Realtime API (native audio)Zero transcription overhead
    Multi-agent handoff with contextAgentHandoff + context objects
    SIP inbound/outbound (PSTN)Twilio, Vonage, Bandwidth
    Video + voice rooms (WebRTC)Unique to LiveKit
    Browser SDK (JS/TS)React hooks included
    Mobile SDK (Swift/Kotlin)iOS + Android native
    DTMF / IVR menu handlingSIP module built-in
    End-to-end call recordingEgress to S3/GCS
    Self-hosted on your infraHIPAA / SOC 2 requirement
    Sub-300ms
    voice latency
    standard pipeline
    Sub-200ms
    with Realtime API
    no STT hop
    10k+
    min/month crossover
    LiveKit vs managed
    3 weeks
    to production
    from kick-off
    What We Solve

    5 LiveKit Pitfalls
    We Fix Before They Hit Production

    01

    Problem

    Worker cold starts

    Impact

    Unprimed LiveKit worker pools add 1–3 seconds to the first call connection. In a production contact centre, that opening silence kills the user experience.

    Our Fix

    We pre-warm worker pools based on historical call volume patterns, configure min_idle_worker thresholds, and implement health-check pings that keep workers hot. First-call latency matches steady-state latency.

    02

    Problem

    Codec mismatch on SIP trunks

    Impact

    SIP trunks default to PCMU/PCMA (G.711). LiveKit Agents process Opus internally. Without explicit codec negotiation, audio quality degrades or calls fail entirely on certain carriers.

    Our Fix

    We configure explicit SDP codec preference in the SIP module, set up transcoding profiles for carrier-specific quirks, and validate against all target trunk providers before go-live.

    03

    Problem

    Multi-agent context loss on handoff

    Impact

    When agent A hands off to agent B, the new agent starts with no conversational context — the caller has to repeat themselves, trust breaks down, and your escalation rate spikes.

    Our Fix

    We build structured context objects passed via AgentHandoff: compressed conversation summary, extracted entities (name, intent, key data), and caller sentiment. Agent B picks up mid-conversation without friction.

    04

    Problem

    Room leak from unhandled disconnections

    Impact

    Rooms not explicitly closed after calls consume server resources indefinitely. At volume, this degrades your LiveKit server performance and inflates cloud costs.

    Our Fix

    We implement webhook handlers for participant_disconnected and room_finished events, enforce max room duration, and run a nightly room audit job that closes any rooms older than the maximum call duration.

    05

    Problem

    OpenAI Realtime rate limit failures

    Impact

    GPT-4o Realtime has strict concurrency limits per API key. An unhandled 429 mid-call causes the agent to go silent — the worst possible UX in a voice interaction.

    Our Fix

    We implement exponential backoff, maintain a fallback pipeline (Deepgram STT + GPT-4o chat + TTS) that activates automatically if Realtime is rate-limited, and distribute load across multiple API keys for high-volume deployments.

    Timeline

    From Kick-Off to Production in 3 Weeks

    Week 1

    Architecture & Pipeline Design

    • Map agent topology: single agent, multi-agent, or supervisor pattern
    • Choose pipeline: VoicePipelineAgent vs OpenAI Realtime vs custom plugin
    • Provider selection: STT, LLM, TTS benchmarked on your audio profile
    • Spec SIP trunk requirements: carriers, codecs, inbound/outbound volume
    Week 1–2

    Infrastructure Setup

    • LiveKit server deployment (Cloud or self-hosted on Kubernetes)
    • SIP module configuration and trunk provider wiring
    • Worker pool setup with pre-warming and autoscaling policies
    • Room service API integration for server-side room management
    Week 2–3

    Agent Build & Integration

    • Agent pipeline implementation with all conversation branches
    • Multi-agent handoff logic with context passing
    • CRM and calendar tool call integration
    • WebRTC SDK integration (web/mobile if applicable)
    Week 3

    Tuning & Production

    • Latency profiling: VAD, STT, LLM, TTS chain optimisation
    • SIP codec validation across all target carriers
    • Load testing: concurrent calls against target peak volume
    • Monitoring, alerting, and runbook handoff
    Ready to Build?

    Ship Your LiveKit System
    in 3 Weeks

    We scope most LiveKit projects in a single 30-minute call. Fixed price, clear deliverables, production-ready in 3 weeks.